VerticaPy

Python API for Vertica Data Science at Scale

Example: Methods in a Time Series Model

In this example, we use the 'commodities' dataset to demonstrate the methods available to time series models.

In [1]:
from verticapy.datasets import load_commodities
commodities = load_commodities()
display(commodities)
📅
date
Date
123
Gold
Float
123
Oil
Float
123
Spread
Float
123
Vix
Float
123
Dol_Eur
Float
123
SP500
Float
11986-01-01345.56136363636422.92545454545451.0514285714285718.12136363636361.12159999999858211.779999
21986-02-01339.052515.45473684210530.73684210526315820.62421052631581.07880000000296226.919998
31986-03-01346.09473684210512.61250.56423.5641.04850000000442238.899994
41986-04-01340.71590909090912.84363636363640.60409090909090923.01545454545451.05259999999544235.520004
51986-05-01342.32515.3776190476190.64238095238095218.88751.03720000000612247.350006
61986-06-01342.79761904761913.42571428571430.61476190476190518.59809523809521.0399999999936250.839996
71986-07-01348.55434782608711.58454545454550.63681818181818219.63909090909091.01029999999446236.119995
81986-08-01376.2915.09666666666670.8395238095238118.63809523809520.979300000000876252.929993
91986-09-01418.15227272727314.86666666666671.1014285714285722.70523809523810.973200000000361231.320007
101986-10-01423.86304347826114.89681818181821.1472727272727322.52391304347830.961600000000544243.979996
111986-11-01396.982515.22157894736840.97388888888888918.63157894736840.967399999999543249.220001
121986-12-01391.59523809523816.1076190476190.84090909090909119.75863636363640.957399999999325242.169998
131987-01-01408.5238095238118.65142857142860.858520.76666666666670.900400000000445274.079987
141987-02-01401.04517.74894736842110.85263157894736823.44631578947370.882600000000821284.200012
151987-03-01408.84772727272718.30285714285710.82409090909090921.83727272727270.883599999999206291.700012
161987-04-01439.66518.67714285714290.99857142857142926.88142857142860.872100000000501288.359985
171987-05-01461.6519.43750.851525.41150.861100000000079290.100006
181987-06-01449.27727272727320.07318181818180.82909090909090921.62454545454550.876500000000306304.0
191987-07-01450.33043478260921.34217391304351.0045454545454517.80090909090910.888600000000224318.660004
201987-08-01460.987520.31095238095241.0076190476190520.84904761904760.89600000000064329.799988
211987-09-01460.12045454545519.531.0780952380952422.89380952380950.873499999999694321.829987
221987-10-01465.76363636363619.85909090909091.1223809523809558.21954545454550.868599999999788251.789993
231987-11-01468.14047619047618.8541.1678947368421149.43650.814700000000812230.300003
241987-12-01487.07857142857117.27454545454551.1341.76409090909090.791400000000067247.080002
251988-01-01477.757517.12951.0357894736842138.33650.800100000000384257.070007
261988-02-01442.1238095238116.79571428571431.031533.6740.822000000000116267.820007
271988-03-01443.49130434782616.19739130434781.1030434782608729.35695652173910.810900000000402258.890015
281988-04-01451.55789473684217.86251.12927.4050.805700000000798261.329987
291988-05-01451.3217.42363636363641.0933333333333325.71666666666670.813099999999395262.160004
301988-06-01451.65681818181816.52772727272730.89545454545454625.27090909090910.842500000000655273.5
311988-07-01437.45238095238115.49750.77723.6440.886300000000119272.019989
321988-08-01431.06363636363615.52347826086960.63173913043478323.70739130434780.905899999999747261.519989
331988-09-01413.43863636363614.53545454545450.51380952380952419.52428571428570.900299999999334271.910004
341988-10-01406.39047619047613.77047619047620.441520.48190476190480.87960000000021278.970001
351988-11-01419.96590909090914.14136363636360.296521.65904761904760.844499999999243273.700012
361988-12-01419.247516.3823809523810.017142857142857117.75428571428570.843999999999141277.720001
371989-01-01404.44523809523818.0242857142857-0.08417.75809523809520.880499999999302297.470001
381989-02-01387.972517.9365-0.20263157894736818.31263157894740.888899999999921288.859985
391989-03-01390.2738095238119.4840909090909-0.32181818181818217.47545454545450.896699999999328294.869995
401989-04-01384.7221.069-0.27616.88750.899199999999837309.640015
411989-05-01371.3520.1234782608696-0.15863636363636417.4350.9375320.519989
421989-06-01367.72727272727320.0504545454545-0.12909090909090916.73227272727270.955400000000736317.980011
431989-07-01375.20952380952419.78142857142860.19918.05650.914000000000669346.079987
441989-08-01365.54772727272718.5778260869565-0.032173913043478319.32347826086960.927799999999479351.450012
451989-09-01361.79761904761919.5914285714286-0.09416.74650.941100000000006349.149994
461989-10-01366.820.09772727272730.028571428571428621.95090909090910.907199999999648340.359985
471989-11-01394.36136363636419.85590909090910.078571428571428620.9323809523810.893899999999121345.98999
481989-12-01409.65526315789521.10.05918.2350.856499999999869353.399994
491990-01-01410.11818181818222.86318181818180.12142857142857123.49909090909090.831899999999223329.079987
501990-02-01416.542522.1130.10263157894736823.32684210526320.820799999999508331.890015
511990-03-01393.66136363636420.3877272727273-0.038181818181818218.83136363636360.835100000000239339.940002
521990-04-01374.92894736842118.42550.061520.45750.82510000000002330.799988
531990-05-01368.85476190476218.19954545454550.11590909090909118.15181818181820.811400000000504361.230011
541990-06-01352.65714285714316.69523809523810.12904761904761917.58285714285710.817699999999604358.019989
551990-07-01361.82045454545518.45409090909090.31428571428571418.93285714285710.792699999999968356.149994
561990-08-01394.86136363636427.30739130434780.69130434782608727.77521739130430.759899999999106322.559998
571990-09-01389.5633.50750.81368421052631628.81894736842110.761699999999109306.049988
581990-10-01381.33260869565236.03956521739130.84181818181818230.13043478260870.739799999999377304.0
591990-11-01381.86590909090932.33227272727270.793525.10666666666670.72400000000016322.220001
601990-12-01378.16052631578927.2810.76122.58450.731999999999971330.220001
611991-01-01384.59090909090925.23409090909090.96761904761904826.93181818181820.736699999999473343.929993
621991-02-01363.747520.47750.98789473684210522.11263157894740.722599999999147367.070007
631991-03-01363.3919.90151.00719.04105263157890.781800000000658375.220001
641991-04-01358.05476190476220.831.0909090909090918.92727272727270.826699999999619375.339996
651991-05-01357.11666666666721.23227272727271.2840909090909117.18045454545450.83389999999963389.829987
661991-06-01366.3620.1891.32817.5750.868700000000899371.160004
671991-07-01368.01304347826121.40304347826091.35517.66954545454550.870699999999488387.809998
681991-08-01356.72142857142921.69363636363641.4668181818181815.93272727272730.850300000000061395.429993
691991-09-01348.45952380952421.88651.468517.0290.828100000000632387.859985
701991-10-01358.82608695652223.23086956521741.61516.84636363636360.82550000000083392.450012
711991-11-01359.95952380952422.46095238095241.8584210526315817.68150.795000000000073375.220001
721991-12-01361.87519.49809523809522.0628571428571418.01857142857140.768099999999322417.089996
731992-01-01354.43636363636418.78545454545452.0742857142857117.49954545454550.770599999999831408.779999
741992-02-01353.852519.01252.1257894736842117.05052631578950.791999999999462412.700012
751992-03-01344.64090909090918.92181818181821.8572727272727316.22272727272730.812700000000404403.690002
761992-04-01338.727520.232.1361904761904816.18857142857140.804899999999179414.950012
771992-05-01337.03947368421120.97552.166514.7280.78859999999986415.350006
781992-06-01340.78409090909122.38454545454552.2136363636363614.75318181818180.767900000000736408.140015
791992-07-01352.45217391304321.77521739130432.4890909090909113.30363636363640.729799999999159424.209991
801992-08-01343.602521.33904761904762.3928571428571414.4223809523810.71349999999984414.029999
811992-09-01345.321.88136363636362.5209523809523814.25857142857140.721999999999753417.799988
821992-10-01344.27727272727321.68590909090912.5061904761904817.47863636363640.755199999999604418.679993
831992-11-01334.92380952380920.33852.2936842105263214.5940.807199999999284431.350006
841992-12-01334.65714285714319.41409090909092.0963636363636412.78136363636360.807199999999284435.709991
851993-01-01328.992519.0322.2112.5840.825000000000728438.779999
861993-02-01329.3120.08611111111112.1605263157894713.62473684210530.845300000000861443.380005
871993-03-01329.97391304347820.32217391304352.0256521739130413.69304347826090.848400000000766451.670013
881993-04-01341.947520.25252.1319047619047613.45666666666670.820100000000821440.190002
891993-05-01367.04473684210519.94952.058513.48550.821200000000317450.190002
901993-06-01371.91363636363619.09409090909091.7990909090909112.97318181818180.844300000000658450.529999
911993-07-01392.03409090909117.891.7333333333333311.86950.878399999999601448.130005
921993-08-01379.79523809523818.01090909090911.6763636363636411.95318181818180.882400000000416463.559998
931993-09-01355.56136363636417.50428571428571.5128571428571412.6490.848200000000361458.929993
941993-10-01364.00476190476218.15333333333331.459511.37523809523810.859300000000076467.829987
951993-11-01373.93863636363616.60904761904761.568513.37095238095240.885800000000018461.790009
961993-12-01383.24285714285714.51476190476191.5618181818181810.86454545454550.885800000000018466.450012
971994-01-01387.1115.02666666666671.610510.60523809523810.897499999999127481.609985
981994-02-01381.657514.78105263157891.4989473684210512.88526315789470.894800000000032467.140015
991994-03-01384.014.68086956521741.4873913043478314.24086956521740.876000000000204445.769989
1001994-04-01377.90789473684216.421.4226315789473715.33473684210530.877300000000105450.910004
Rows: 1-100 | Columns: 7

Let's create a VAR model to predict the change in our variables over time.

In [3]:
from verticapy.learn.tsa import VAR
model = VAR("VAR_commodities", p = 15)
model.drop()
model.fit(input_relation = "commodities",
          X = ["Gold", "Oil", "Spread", "Vix", "Dol_Eur", "SP500"],
          ts = "date")

Fitting the model creates new model attributes.

In [4]:
model.X
Out[4]:
['"Gold"', '"Oil"', '"Spread"', '"Vix"', '"Dol_Eur"', '"SP500"']
In [5]:
model.ts
Out[5]:
'"date"'
In [6]:
model.input_relation
Out[6]:
'commodities'
In [7]:
model.test_relation
Out[7]:
'commodities'

Since we didn't write a test relation when fitting the model, the model will use the training relation as the test relation. After fitting the model, the These attributes will be used when invoking the different model abstractions. For example, let's compute the R2 of the model.

In [8]:
model.score(method = "r2")
Out[8]:
r2
"Gold"0.9969178988297
"Oil"0.984505390437316
"Spread"0.98333383705978
"Vix"0.809280825408277
"Dol_Eur"0.976525112259812
"SP500"0.995213614862105
Rows: 1-6 | Columns: 2

The 'score' method uses the 'y' attribute and the model prediction in the 'test_relation' to compute the accuracy of the model. You can change these attributes at any time to deploy the models on different columns.

Models have many useful attributes. For example, the 'coef_' attribute gives us the p-value of the model.

In [9]:
for elem in model.coef_:
    display(elem)
Abc
predictor
Varchar(65000)
123
coefficient
Float
123
std_err
Float
123
t_value
Float
123
p_value
Float
1Intercept28.536246891519123.45761671585351.216502393963720.224719007474869
2ar0_11.212495463112090.058300326851587720.79740421007739.38585656197178e-61
3ar0_2-0.2657172763833840.0911043814875882-2.916624557948230.00379668763754037
4ar0_30.1236049240760760.09244348250144171.337086409246310.18217474351721
5ar0_4-0.08465352359058540.0922931959314058-0.9172238834756760.35973835612789
6ar0_50.1475883108740850.09347587727798361.578891957709880.11538065396013
7ar0_6-0.07467377115272230.0964409915451842-0.7742949336821830.439346523264487
8ar0_70.03003985021706510.09494504694901030.3163919675893980.751917949570274
9ar0_8-0.2825957175900340.0934137195443952-3.025205708201450.00269259813755072
10ar0_90.2114659166363810.09457464049068482.235968495774610.0260652425208447
11ar0_10-0.0289682147487440.0955704715244925-0.3031084213215390.762010542572336
12ar0_110.1524238528568420.09477266262891351.608310335794450.108785149004158
13ar0_12-0.1609365867255260.094521878486629-1.702638471666560.089638133407115
14ar0_130.08667056505930760.09481950266658470.9140584228127490.361396529767663
15ar0_140.02827987223163570.09418508373997560.3002585028188780.764181233977993
16ar0_15-0.106574371683990.0616194550652301-1.729557192142830.0847048269578117
17ar1_10.1863309243810110.4465079686132980.4173070526819290.67674268420536
18ar1_2-0.3838352151493040.719190789680871-0.5337042974641330.593928600425446
19ar1_3-1.233452950335280.730929242853722-1.687513480127820.0925104852369963
20ar1_42.172177349679370.7351186813212162.954866207148150.00336774173477664
21ar1_5-0.8972704694919860.751437855340256-1.194071423359020.233362918851882
22ar1_6-0.7221964401502420.75015814215371-0.9627255902026340.33643560184064
23ar1_70.7292592706094180.7363193796618120.9904116213053680.322745378832708
24ar1_80.6531397262352240.733784878425530.8900970099529110.374104035524252
25ar1_9-1.382407119715480.741297102456291-1.864848945361950.0631473354628441
26ar1_101.421271557902510.7433760832690831.911914561001620.0568088195382841
27ar1_11-0.4859731638262020.746682470054503-0.6508431405798630.515629858830073
28ar1_12-0.7995376859789760.747637946531285-1.069418278845370.285713217588517
29ar1_130.6870730341147460.7455300836061860.9215899522006160.357459156835338
30ar1_14-0.7877873503674660.744855541380698-1.057637765448030.291044074790766
31ar1_150.7160574430496350.4725560433692681.515285759429150.130719006743371
32ar2_1-2.7932478764123513.5713219264952-0.2058198819202070.837066706683407
33ar2_212.860637429672421.88327013108650.5876926689947990.55716643483518
34ar2_3-5.6644193120846522.6755409970521-0.249803050468390.802905111952815
35ar2_424.180697465100823.18614932345571.042894062647950.297809959015635
36ar2_5-44.53895138947723.6750258753874-1.881263050097860.0608731390576656
37ar2_617.201770091087423.90236728391570.7196680515683780.472271605925185
38ar2_718.333591040283923.81724502985770.7697611968680920.442027712401021
39ar2_8-10.334662689334423.5469658756951-0.4388957262643230.661042831989565
40ar2_9-18.930740950043923.4188393201874-0.8083552174050420.419506019701915
41ar2_107.1386040815850723.40278862908090.3050321991420490.76054632453699
42ar2_118.8682682917860823.24458586626820.3815197372328950.703078993345408
43ar2_12-2.9038816524844223.0213247115647-0.1261387730231550.89970384535311
44ar2_13-5.2941515294082822.5976584117239-0.2342787660982440.814923221458952
45ar2_14-3.2404902134367121.6450388143914-0.1497105291066590.88109035429166
46ar2_158.3027573591061813.41958084900610.6187046713699050.536565284150822
47ar3_1-0.5027462314382090.510054281970306-0.9856720141553050.325062760565841
48ar3_21.12411961964040.6280470440443211.78986531391280.0744514757095814
49ar3_30.06391420005229520.6292719945663250.1015684800915750.919164861770739
50ar3_4-0.805497838790870.620317126196823-1.298525874546450.195071822840087
51ar3_50.6091150609886430.6242358391386760.975777138699860.329935733930905
52ar3_6-0.04453454311715180.656703707290886-0.06781527593451710.94597640165073
53ar3_7-1.174309257422690.683845863352519-1.717213366862680.0869389378836803
54ar3_80.7024618181908560.6818779363461291.030187047780170.303725291101653
55ar3_9-0.8503067836692250.688606542738108-1.23482239986880.217831730394892
56ar3_101.242028899205760.6985074602923091.778118301966310.076364539869516
57ar3_11-0.2810453517158180.70794423948742-0.3969879773572370.691649495689552
58ar3_120.2439018755034110.7071052295158240.3449300971376190.730380829654549
59ar3_131.088345939898770.711864680652131.528866327378050.127317295238838
60ar3_14-0.8170926826928730.688290205843594-1.187133967265180.236083662488294
61ar3_15-0.317155618971810.502041192339552-0.6317322638284720.528027414824921
62ar4_1-46.608095483796295.4243667945713-0.4884297066820860.625590823194623
63ar4_2-92.9647046344762153.445373485837-0.6058488602333560.545058446285002
64ar4_3234.503308695101159.145376352351.47351631615050.141626537557194
65ar4_4-140.101600778959159.318926408608-0.879378263067360.379877356433741
66ar4_532.352148242775159.4637317923710.2028809176803850.839361203541782
67ar4_6-15.6352645152074160.642067356053-0.09732982631848730.922527366752222
68ar4_7112.90352543657161.2823329396930.7000365345582320.484429490600711
69ar4_8-172.016837197269160.406214041056-1.072382626980030.284382315124078
70ar4_982.7850488694094161.3999277571030.5129187479810770.608373459980389
71ar4_10-124.571371472994160.584913041091-0.7757352114461560.438496730959977
72ar4_1181.6149826794426160.0790596517880.5098417173175290.610525132819986
73ar4_1288.0632092895976160.8982113679150.5473224875584830.584551003184447
74ar4_13-199.332941775472160.146804337156-1.244688850336450.214186303391015
75ar4_14358.387652307923154.1002128247172.325679152147410.0206805893591999
76ar4_15-242.53992666257591.833173804137-2.641092718627670.00868270462061203
77ar5_1-0.06438235093784430.0375621688308582-1.714021126622290.087524415311534
78ar5_20.09537027877085080.04848754643294171.966902551003440.0500860818582451
79ar5_30.08893043290304090.04985671819359551.783720150967830.0754472822621015
80ar5_4-0.07727055770613590.0498135645032031-1.551195110744730.121875209388849
81ar5_5-0.07429311124477070.050296861260262-1.477092394699140.14066602430672
82ar5_60.04498200516937350.05292886014082780.8498578100811140.39606001252256
83ar5_7-0.04690586717959630.0530494310654534-0.8841917102131220.377277965115729
84ar5_8-0.04512938692550250.052816929499234-0.854449271348820.393515924634555
85ar5_90.01642055844626710.05204980922706130.3154777834945430.752611187849938
86ar5_100.1015015644999830.05229986801992821.940761388944760.0531935246033809
87ar5_11-0.01711949714616880.0522072523665041-0.3279141569448410.743197926015103
88ar5_120.01577646920815570.05244384781240790.3008259284213520.763748895009399
89ar5_130.03625698244010780.05272836615243270.6876181661933590.492207405051925
90ar5_140.01513946647662580.05277874448593720.2868477949614670.774420491492481
91ar5_15-0.07730205588347870.0426604647957568-1.812030324882150.0709489757714002
Rows: 1-91 | Columns: 5
Abc
predictor
Varchar(65000)
123
coefficient
Float
123
std_err
Float
123
t_value
Float
123
p_value
Float
1Intercept-0.003312827053605363.20498795635841-0.00103364727066540.999175933785173
2ar0_10.007272143575888460.00796550850303630.9129540911438930.361976146683964
3ar0_2-0.01275801034824920.0124474898271258-1.024946437027550.306187577961975
4ar0_30.02237247520105610.01263044970210951.771312639590310.0774911865400367
5ar0_40.005636245021345850.01260991621600120.4469692680585620.655209359904166
6ar0_5-0.02245536498673940.012771504646655-1.75823958163150.0796935374323065
7ar0_60.006882045767881740.01317662489525980.5222919998547960.601840057485922
8ar0_7-0.004671453260382210.0129722356569074-0.3601116556878750.719008857075765
9ar0_8-0.008462359800899930.0127630121049804-0.6630378261255220.507799032765273
10ar0_9-0.001407847661806130.0129216274364615-0.108952813314640.913310406863298
11ar0_10-0.0005919017415867420.0130576867176998-0.04532975513835960.963873656391934
12ar0_110.01733286484210960.01294868297990411.338581295797390.181687870589536
13ar0_12-0.01717115857800610.0129144186228126-1.329611427313820.184623881195283
14ar0_130.005170984476465360.01295508268190410.3991471612673130.690059600334008
15ar0_140.000119673282942490.01286840273296910.009299777557931460.992585939849527
16ar0_150.002914003940854390.008418997281508150.3461224470584920.729485485412894
17ar1_11.305046501643040.061005884747725521.39214121784695.37470853731338e-63
18ar1_2-0.2987529681969720.0982622338480484-3.040364100199060.00256445086731384
19ar1_3-0.09447111773852870.099866045586512-0.9459783571453250.344896380826558
20ar1_40.06619912520982750.1004384438823350.6591014620594950.510319898222507
21ar1_5-0.03684711505161790.102668114390737-0.3588954104229880.719917642984825
22ar1_6-0.008448944626650250.102493268608228-0.08243414168930070.934354687631606
23ar1_7-0.0008208927465602760.100602493954746-0.008159765372511910.993494769929288
24ar1_80.05656951766295040.1002562078833150.564249524865230.572992330624243
25ar1_9-0.03170342732905240.101282594657202-0.3130195018833670.754476329588307
26ar1_100.06064534165106750.1015666434822470.5970990038837670.55087713138308
27ar1_11-0.04003057820187910.102018391413621-0.3923858987305550.695042748561787
28ar1_120.0603260907884220.1021489370968310.590569931542570.555238901629821
29ar1_13-0.1323432549371830.10186094214106-1.299254180801810.194822152956317
30ar1_140.04269559906647660.1017687801906390.4195353328053720.675115523934597
31ar1_150.04669920358976040.06456480409108690.7232919583226490.470045915218135
32ar2_1-2.583653176637991.85423454791482-1.393379914932250.164503151458173
33ar2_23.817541191953752.98988674192421.276817993947460.202622091538284
34ar2_3-0.681391066442873.09813382492293-0.2199359695057140.826065780979161
35ar2_42.069176225354343.167897669918910.6531701591886660.514130715207167
36ar2_5-2.648490280641453.23469232685557-0.8187765676051290.413542869255162
37ar2_6-0.9317941970944053.26575372943286-0.2853228609054430.775587337371381
38ar2_72.581080422784793.254123570990990.7931722217908180.428284133770991
39ar2_8-5.087006662358253.21719563221363-1.581192828755050.114853671333204
40ar2_93.42489845739823.199689844125011.070384513576120.285278943559098
41ar2_10-0.8065558629584763.19749685613689-0.2522460222002940.801018066971676
42ar2_11-2.065776302946693.17588178945645-0.6504575547505640.51587848616302
43ar2_123.403484107655973.145377867399281.082058897575350.280067337184685
44ar2_13-0.3855369864626543.08749281432879-0.1248705696328780.900706952631226
45ar2_14-0.05520041922090972.95733746336432-0.01866558007151230.985119894286093
46ar2_15-0.1296921240098071.83350233407877-0.07073463807449710.943654562153457
47ar3_1-0.0526793224295190.0696881465242403-0.7559294522375490.450265515763487
48ar3_20.03748313874157820.08580936574124210.4368187367170210.662546913752644
49ar3_3-0.02011651031082810.0859767293620956-0.2339762219391520.81515788098011
50ar3_4-0.07238217131239820.0847532357044628-0.8540343116196430.393745440537419
51ar3_50.1675272515487480.08528864507427211.964238632268810.0503955849597349
52ar3_60.02580325690679790.08972469361479330.287582558014370.773858449582504
53ar3_7-0.1113687750393590.0934330960642349-1.191962802589720.23418750780549
54ar3_80.1841358694532060.09316422039664791.976465521519370.0489881830529803
55ar3_9-0.2398210225536630.0940835423682955-2.54902203421370.0112841409772017
56ar3_100.1856601149010830.09543629366875761.945382702575140.0526326906844688
57ar3_11-0.1151733807789060.0967256302639243-1.190722463783850.234673517735206
58ar3_120.0797702686185850.09661099726915740.825685179466120.409617669227945
59ar3_13-0.09005887781435720.0972612757588912-0.9259479388036340.355193308061036
60ar3_14-0.04573985387992250.0940403216119267-0.4863855535147550.627037494168276
61ar3_150.07627900530684430.06859332704317891.112047025490210.266979586354225
62ar4_1-8.9473093793076313.0377245917329-0.6862631064458150.493060165037644
63ar4_27.3947889423034220.96506989342430.3527194986658640.724538437350074
64ar4_3-8.4147827287597521.7438549149238-0.3869959012182470.699024772876226
65ar4_421.722639037390821.7675668651560.9979360197653920.319088694622401
66ar4_5-25.227534432873721.7873514629093-1.157898172057350.247796903117786
67ar4_611.620196573051521.94834613410270.5294338125548520.596883471476571
68ar4_78.3255395637461322.03582490525390.3778183752840190.705824079790489
69ar4_8-30.725496430084121.9161217592572-1.401958647957680.161928084882079
70ar4_926.663639794627722.05189175373611.209131628814130.227533648561226
71ar4_10-16.417369753726221.9405372039235-0.7482665351872260.454866703093321
72ar4_1135.394510208010821.87142302066951.618299375150920.106615048893171
73ar4_12-31.925415567699921.9833428041845-1.452254820937560.147442119945856
74ar4_1320.170556635521321.8806789013220.9218432721620280.357327198344179
75ar4_14-13.54281943605221.0545398604667-0.6432256190732940.520553220367178
76ar4_154.4516015042117912.54706390685940.354792287443290.722986450135791
77ar5_10.009696274750559230.005132077149007231.889347036108940.059778398384304
78ar5_2-0.01699882959686950.00662479928090568-2.565938812042860.0107594772510146
79ar5_30.002770914380411330.006811867688418530.4067774811777990.684452128058598
80ar5_4-0.008346424935787410.00680597164792749-1.226338481490590.221002007160034
81ar5_50.02227488816045660.006872003943726493.241396300534950.00131887541129843
82ar5_6-0.001867506954123850.0072316110093352-0.2582421747675740.796391373792244
83ar5_7-0.00259537264451870.00724808448002035-0.3580770411372760.720529357533611
84ar5_80.002459613694269170.007216318050864580.3408405334870860.733454511803387
85ar5_9-0.008279044727722340.00711150726538822-1.164175809538510.245247944881215
86ar5_100.004955757181619450.007145672518799420.6935326477083070.488494655545902
87ar5_11-0.001084923153815250.00713301854557657-0.1520987428930850.879207996253276
88ar5_12-0.003678964877886550.00716534431693842-0.5134386730292510.60801022789806
89ar5_13-0.00357489323141280.00720421773976686-0.4962222632000140.620089253817064
90ar5_14-0.00020859300637710.00721110087517226-0.02892665211428170.9769417024462
91ar5_150.00398787521617550.005828651628988720.6841848629864680.4943695795084
Rows: 1-91 | Columns: 5
Abc
predictor
Varchar(65000)
123
coefficient
Float
123
std_err
Float
123
t_value
Float
123
p_value
Float
1Intercept-0.08043183988287690.100242229731371-0.8023748084855870.422950861457032
2ar0_10.000105988395660520.0002491367656169940.4254225400977510.670823851912084
3ar0_2-0.0005858106883871310.000389319445757727-1.504704413741720.133418235876387
4ar0_30.0005607519953661770.0003950418715731981.419474834738560.156765382046698
5ar0_40.0003085764579803250.0003943996468723010.7823953708564960.434579471686117
6ar0_5-0.0006606686988079870.000399453639214266-1.65393085442290.0991537432362838
7ar0_60.0001972617510490990.0004121245626568680.4786459457242740.632527936851413
8ar0_71.3500852206666e-050.0004057318918373420.03327530440244140.973476461418362
9ar0_80.0005654333328524930.0003991880184615091.41645867787240.157645310092673
10ar0_9-0.0005829705764201880.000404149021346311-1.442464402061850.150180979571038
11ar0_10-0.0001440225925234680.000408404539904473-0.3526468940750650.724592820236949
12ar0_110.0003551410965170090.0004049952360710480.8769019111491640.381218952705149
13ar0_120.0001789000344283310.0004039235516834840.4429056777766640.658142859893796
14ar0_130.0001698304159006850.0004051953991939160.4191321427601120.675409833223998
15ar0_14-0.0008138737658184990.000402484315260819-2.022125421933740.0440219694537639
16ar0_150.0003482709771269050.0002633205088731861.322612426268060.186939185193719
17ar1_10.0009971439623117220.001908077658050070.5225908694569260.601632261442651
18ar1_2-0.001809837206331540.00307334241296358-0.5888823837843510.556369025158628
19ar1_30.002118780524276160.003123504743344250.6783343386274620.498065763495443
20ar1_4-2.10470818869934e-050.00314140761294908-0.006699888865181340.994658611539072
21ar1_5-0.002202677476581570.00321114489320472-0.6859477070756830.493258764769414
22ar1_60.0007168367402825560.003205676251407480.2236148269706970.823204314192409
23ar1_7-0.0007804947151395240.00314653859792313-0.248048670260930.804260975878767
24ar1_8-3.6045724954803e-050.00313570782776181-0.01149524347762070.990835718867679
25ar1_9-0.00191185073772560.00316781006969912-0.6035244208650370.546601211341372
26ar1_100.002763025202120680.003176694248973060.8697800246321770.385093589114493
27ar1_110.003088382325311170.003190823543851550.967895053696160.333851295374327
28ar1_12-0.001702520070322010.00319490661391142-0.5328857071780480.594494485370403
29ar1_13-0.001785145120628110.00318589901172662-0.5603269639299190.575661142375222
30ar1_14-0.0001475505483794490.00318301646753852-0.04635557179305220.963056694620022
31ar1_150.001868278657414120.002019389780051930.925169908191810.355597160410365
32ar2_11.271530105764080.057994790638500821.92490207766955.39776715568308e-65
33ar2_2-0.4574180260770220.0935145210327989-4.891411740392591.61109991524605e-06
34ar2_30.353570793382030.09690015901629973.648815409297270.000309014221509024
35ar2_4-0.3059207899235080.0990821589090473-3.087546671286490.00220059246934958
36ar2_50.1408342687981590.1011712916723041.392037864400540.16490878086164
37ar2_60.06627779395289220.1021427974299950.6488738865637260.516900297015444
38ar2_7-0.07386195180284720.101779041612433-0.7257088555039480.468564774910838
39ar2_80.04466769324540820.1006240485288920.4439067389798270.657419701917299
40ar2_9-0.02388318553029030.100076520970254-0.2386492385900310.811535263729991
41ar2_10-0.02909739639416390.100007931007141-0.2909508886058860.771283442985183
42ar2_11-0.08996286915013480.0993318777709533-0.9056797391626660.365808758310635
43ar2_120.09695032012335150.09837780830042810.9854897338969240.325152101325999
44ar2_13-0.0587318445059970.0965673407208563-0.6081957323001260.543502999430893
45ar2_140.11005870853020.09249647906090431.189869167427790.235008286822051
46ar2_15-0.09527901283227540.0573463503415347-1.66146602643110.0976307962623087
47ar3_16.42029951969381e-050.002179632275864670.0294558838698920.976519957312155
48ar3_2-0.004029085680316010.00268385475105196-1.501230898854260.134313692898461
49ar3_30.002727315678281440.002689089373696011.014215334365360.31127093467648
50ar3_40.001448338109383720.002650822230738430.5463731564452220.585202471344428
51ar3_50.002011358674245620.002667568199765320.7540045928057510.451418796474799
52ar3_6-0.00381365018129820.00280631424279373-1.358953364218270.175149241984144
53ar3_70.004145618863806710.002922301739575371.418614240844650.157016067728795
54ar3_8-0.004480725655603610.00291389213030181-1.537711574497960.125139187067268
55ar3_90.00279545774546430.002942645712385070.9499810778099190.342861888477791
56ar3_10-0.00520090148056590.00298495563943528-1.742371448290550.082435172104692
57ar3_110.002031533976465270.003025282148281390.6715188458105810.502390146924729
58ar3_120.002103477929593980.003021696778491340.6961247549941780.4868722832595
59ar3_13-0.0009328209862657920.00304203550258168-0.3066436882390540.759320457299259
60ar3_14-0.0008017444247716550.00294129389919635-0.2725822213790730.785355856920147
61ar3_150.001301375385017960.002145389667958080.6065916157117360.54456592680126
62ar4_1-0.02522871174943480.407780185602883-0.06186841008994920.950707493721872
63ar4_20.2695627850148410.6557233228978380.4110922634619160.681288917699377
64ar4_3-0.7031269696984170.68008133862193-1.033886580571650.301995057196506
65ar4_40.4666916703328350.6808229759681290.6854816696942420.493552296582137
66ar4_50.216320552668250.6814417777296750.3174453926041260.751119372367432
67ar4_6-0.04463365747724880.686477199090084-0.06501841217218880.948201248048382
68ar4_7-0.4344287779492790.689213267741124-0.63032561658760.52894592558106
69ar4_80.6733428836611640.685469319113560.9823092950854780.326713508534969
70ar4_9-0.6426359429962640.689715789665868-0.9317402220233190.352195856452096
71ar4_100.2214943436692640.6862329596159750.3227684426484190.747088202622181
72ar4_11-0.05021379561166840.684071279157333-0.07340433247471490.941531709981059
73ar4_120.1184608465023590.6875717879902430.1722886956264120.863322993657085
74ar4_130.9879153380627770.684360774820771.443559266413980.149872769914603
75ar4_14-1.143634736736660.65852167007182-1.736669860252180.0834388419440965
76ar4_150.2414918693952190.3924338187013590.6153696697047240.538762103908763
77ar5_1-0.0001151727140303350.000160515691033808-0.7175168563805840.473595557341566
78ar5_2-4.86758404893289e-050.000207203477979779-0.2349180668390090.814427421448386
79ar5_3-9.0394457670423e-050.00021305440613824-0.4242787525913480.67165681451572
80ar5_40.0001906305662738720.0002128699960083250.8955257661883770.371200923019162
81ar5_50.0003567326251148890.0002149352844447581.659721092497380.0979817860645985
82ar5_6-0.0003567033151313380.000226182694598752-1.577058385320460.115801974721429
83ar5_7-9.11669814708666e-050.000226697934423481-0.4021517959690050.687849451603842
84ar5_80.0001159291817269950.0002257043775887790.5136328456075060.607874599207844
85ar5_90.0002734510689876480.0002224262164914171.229401251799830.219853697050717
86ar5_10-0.0005403347186117290.000223494801218695-2.417661241627710.0161971302740111
87ar5_117.17009755965073e-050.0002230990236032750.3213863262979110.748134222645306
88ar5_122.6267235678154e-060.0002241100749529910.01172068488382950.990655999800992
89ar5_130.0003859979755245490.0002253259168327961.713065150028790.0877003681991129
90ar5_14-0.0004062566511668920.000225541200275347-1.80125250140960.0726347446991492
91ar5_150.0002211727234582290.0001823024122315541.213218852953540.225969775696306
Rows: 1-91 | Columns: 5
Abc
predictor
Varchar(65000)
123
coefficient
Float
123
std_err
Float
123
t_value
Float
123
p_value
Float
1Intercept-1.452711378309463.40700076849687-0.4263900941091890.670119548423146
2ar0_10.006928281203756770.008467580521628070.8182126152872610.413864269511716
3ar0_2-0.00877072990022310.0132320645145451-0.662839112564940.507926132253625
4ar0_30.007600636353459980.01342655648866840.5660897758762410.571742306292973
5ar0_4-0.01327625717338080.0134047287614184-0.9904159501975570.322743267226626
6ar0_50.0127340650002530.01357650223293030.9379488753271080.349000859783346
7ar0_6-0.01015057657424650.014007157516858-0.7246706951092690.469200669575011
8ar0_70.008150775774712570.01378988547040380.5910691421046230.554904804486831
9ar0_80.005435187789711530.01356747439993820.4006042414007630.688987468393517
10ar0_90.01094268614990430.01373608737559060.7966377797908990.426271101595981
11ar0_10-0.03144598346765550.013880722576113-2.265442832332810.0241752072288372
12ar0_110.01416862495353850.01376484825037581.029333901530790.304125236172332
13ar0_120.0007631424347982470.01372842418497140.05558849468197990.955705439560824
14ar0_130.01572410587205940.01377165133042761.141773451475490.254429363705873
15ar0_14-0.02744076913287640.0136795078788277-2.00597633891110.0457272891903616
16ar0_150.007615236967491780.00894965304040090.8508974519028560.395483083801826
17ar1_1-0.08701755986113340.0648511317510514-1.34180479987880.180641302978825
18ar1_2-0.008928797960681580.104455776680954-0.08547921660621420.931935597173597
19ar1_30.06146185841248730.1061606778849130.5789512617762040.56304247926448
20ar1_40.1303586632741640.1067691548777471.220939356721770.223036784837816
21ar1_5-0.02149418244132480.109139363202727-0.1969425311873890.844001567159818
22ar1_6-0.09357163812424040.108953496758457-0.8588217992827050.391102413752327
23ar1_70.1539490726155940.1069435451501561.439535900922670.151007753810314
24ar1_8-0.1450148696764730.106575432406037-1.360678220136020.174603839226149
25ar1_9-0.1050936666973450.107666513113679-0.9761035595755060.329774225681084
26ar1_100.08674570351864830.1079684657507550.8034355486619670.422338641249122
27ar1_110.2040026343355240.1084486876955211.881098228761220.0608956317800361
28ar1_12-0.1731722849104040.108587461771767-1.594772380575420.111782115152717
29ar1_130.002234864594669260.1082813142763640.02063942989244920.983546564650581
30ar1_14-0.000570271788191690.108183343288583-0.005271345577391410.995797484776542
31ar1_150.03145046923861370.0686343724692560.4582320506055710.647106787751489
32ar2_11.96610683654871.971108352275120.9974625871172190.319317965537168
33ar2_2-2.026005660933153.1783415620159-0.6374411375875330.524308043762149
34ar2_30.6831151015181833.293411540432690.2074186882300280.835819076071627
35ar2_40.3583895946193253.367572653282760.106423715690280.91531501284783
36ar2_5-5.014311483344963.43857742790701-1.458251730104870.145783537360451
37ar2_64.306695195473593.471596654154481.240551718564350.215709459946285
38ar2_7-1.343319069188233.45923343803987-0.3883285396169740.698039466114202
39ar2_84.578527631548813.419977903383691.338759419181880.181629921934727
40ar2_9-3.377711498480723.40136871224687-0.9930447958549840.321462605271899
41ar2_10-0.293585475903913.39903749856914-0.08637312063414960.931225574386222
42ar2_11-1.62635918583223.37606001790645-0.4817329008388690.63033560172394
43ar2_122.280024490723893.343633410597440.681900259609050.495811166199507
44ar2_131.350024643700933.282099818901910.4113295506510840.681115122679483
45ar2_14-0.9429952674137783.14374067783863-0.299959622643590.764408989664777
46ar2_15-1.798783411770331.94906937133856-0.9228934784065570.356780457643547
47ar3_10.6835651295170330.07408064304646579.227310960142184.45024233961544e-18
48ar3_20.02304599388370930.09121799488969660.2526474508848520.800708099331744
49ar3_30.04219018503705030.09139590756600950.461620067688250.644677554547664
50ar3_4-0.0529223400847840.0900952961788322-0.5874040302807520.557359980019262
51ar3_50.1308888527072510.09066445280570241.443662302663990.149843789685515
52ar3_6-0.05493254195426540.0953801088370023-0.57593289234070.565078406001292
53ar3_7-0.001682127480485460.0993222546943924-0.01693605814387980.986498521393781
54ar3_80.01391649546693260.09903643159035180.1405189508896680.888341240118434
55ar3_90.05119424944134820.1000136991203860.5118723724009650.609104777313398
56ar3_100.007793769405169290.1014517153572690.07682245073652020.938814347292164
57ar3_11-0.02105820654609580.102822319812075-0.2048019008380980.837861304374464
58ar3_120.0524778146291540.1027004614130470.5109793462182740.609729228598734
59ar3_13-0.01275096341206710.10339172744725-0.1233267276491970.901928295930946
60ar3_14-0.02171348533539690.0999677541270914-0.2172048929677060.828191555134588
61ar3_150.01542564736175220.07291681626641770.2115513012168720.832596116038682
62ar4_1-2.1195308319813.8595022222658-0.1529297948792770.878553132541763
63ar4_26.0313771823366622.28651408713730.2706290072442360.78685647781677
64ar4_3-7.1182416428273423.114386516885-0.3079571953003150.758321715548568
65ar4_42.3678940610379923.13959304925380.1023308428976170.918560235099357
66ar4_517.458729530028923.16062468515010.7538108219172060.451534987379163
67ar4_6-21.127070955574723.3317669720943-0.9055066845491590.365900243796426
68ar4_718.407372305687423.42475959627810.785808376390430.432579963570325
69ar4_8-14.247689276860523.297511470558-0.6115541264939750.54128100973686
70ar4_9-17.903442757280623.441839150358-0.7637388279326680.445603768447186
71ar4_1027.263713171673823.32346583914651.168939185955540.243326206651324
72ar4_11-9.6396688239025323.2499953367088-0.414609494939670.678714556060146
73ar4_124.8753600783343223.36896950873010.2086253771914510.834877709360202
74ar4_139.9938537126608923.25983462251130.4296614260098240.667740435565694
75ar4_14-15.352788334335922.3816234137936-0.6859550824572470.493254120169662
76ar4_156.7893081771571813.33791482374880.5090232069160070.611098062760859
77ar5_1-0.02163554402218070.00545555584880255-3.965781786823719.0902139491336e-05
78ar5_20.02952106971195080.00704236538437064.191925312121423.61250424347636e-05
79ar5_3-0.006322748432389560.00724122485493221-0.8731600743046870.383251678489617
80ar5_4-0.003173895093015130.00723495718255478-0.4386888564687230.661192578192503
81ar5_5-0.0009474661789798940.00730515154384294-0.1296983605738410.896889193432116
82ar5_60.004662235535133120.007687424914466730.6064755866895560.544642850737489
83ar5_7-0.006456767648526760.00770493672045426-0.838003981445560.402674106338948
84ar5_80.003943942459781580.007671168029270440.5141254167204920.607530601286335
85ar5_90.01030049419737360.007559750940804861.362544120570850.174015273594612
86ar5_10-0.01380531094324680.00759606965594914-1.817428165950880.0701168867789674
87ar5_110.01895310453003320.007582618093234452.499546238118470.0129520005138939
88ar5_12-0.01187028479864550.00761698138238616-1.558397507192920.120159326484956
89ar5_130.007911624620331460.007658305026422891.033077762381430.302372769119886
90ar5_14-0.004828190749952560.00766562201105285-0.6298498338413920.52925678641344
91ar5_15-0.006737254062365140.00619603594449338-1.087349092665090.277727255991378
Rows: 1-91 | Columns: 5
Abc
predictor
Varchar(65000)
123
coefficient
Float
123
std_err
Float
123
t_value
Float
123
p_value
Float
1Intercept0.0354998285871240.01434772995274082.474247055391680.0138867718343291
2ar0_1-4.60080793317219e-063.56590934175246e-05-0.1290220107197430.89742390039477
3ar0_2-3.15217005695395e-055.57235237888419e-05-0.5656803164313060.572020326424345
4ar0_32.84796113123736e-055.6542577998779e-050.5036843440882480.614840947128705
5ar0_4-3.42357211732779e-055.64506559954264e-05-0.6064716267611060.544645476152963
6ar0_51.67140788424475e-055.71740369248017e-050.2923368672467660.770224629208652
7ar0_62.69364774890436e-055.89876337321901e-050.4566461779317670.648245171611041
8ar0_71.85031849288808e-055.80726469562463e-050.318621345826060.750228225702234
9ar0_89.10809884623748e-065.71360184685023e-050.1594108075846860.873449034131104
10ar0_92.15412976163169e-055.78460897615755e-050.3723898660238540.709857050367748
11ar0_10-5.47402361367605e-055.84551846634449e-05-0.9364479207777180.349771556269666
12ar0_11-4.06659009801521e-055.79672089783478e-05-0.7015328441178150.483496856968678
13ar0_121.74448172202551e-055.78138181546545e-050.3017413098991230.763051593841938
14ar0_132.10652253919003e-055.79958584451553e-050.3632194773325220.716688489135136
15ar0_14-8.10273823884447e-055.76078193896044e-05-1.406534447007150.160567135720254
16ar0_158.41493935374166e-053.76892210244643e-052.23271777049450.0262813532095582
17ar1_1-0.0005931033209061880.000273104289877873-2.171710012945650.0306354883760566
18ar1_20.0008702699859654550.0004398893271994591.978383952859230.0487703951142936
19ar1_3-0.00060194554843640.000447069091376999-1.346426223701510.179148733564332
20ar1_4-8.28817400997384e-050.000449631539749881-0.1843325762820010.853873083586784
21ar1_50.0007276810421983640.0004596130781437081.583247032780990.1143847937391
22ar1_6-0.0001286859145542830.000458830348191219-0.2804651328352260.779307746857063
23ar1_79.26004123653623e-050.0004503659406804730.20561149057020.837229355555509
24ar1_80.0002509203959494830.0004488157261065220.559072201248870.576516095082301
25ar1_9-4.33854242426479e-050.000453410539085328-0.0956868455906870.923831113604338
26ar1_10-0.0007262057585731840.000454682136947983-1.597172397067940.111246089671872
27ar1_117.83958545191865e-060.0004567044713262430.01716555441017020.986315584157738
28ar1_120.0004565960466851320.0004572888835720020.9984849032815790.318823020407186
29ar1_132.12974059849991e-050.0004559996201147190.04670487659538220.962778516654371
30ar1_14-0.0006111884255431970.000455587039850906-1.341540412877440.18072697116767
31ar1_150.0002833461328027860.0002890364600942480.9803127699197330.327696180708432
32ar2_10.0004237537233517940.008300828871991330.05104956744520110.959318900394391
33ar2_2-0.007790119918155370.0133847890059314-0.5820129039541250.560981003828063
34ar2_30.002954718580880920.01386937738385540.2130390210825430.831436555487222
35ar2_40.006715472710926210.01418168832607950.4735312578105910.63616749950061
36ar2_5-0.01720805474791830.0144807071408342-1.18834353740870.235607675378511
37ar2_60.01586244157970640.01461975933766011.085000184568370.278764622742172
38ar2_7-0.01634725143276050.0145676947511768-1.122157740945240.262663780739483
39ar2_80.0183557480754910.01440237990428711.274494090384820.203442881382926
40ar2_9-0.001753086024873780.0143240119592197-0.1223879196599940.902671107209436
41ar2_100.005114509043274040.01431419463701090.357303304375220.721107875522558
42ar2_110.003741902827234970.01421743073528510.2631912120344110.79257804763226
43ar2_12-0.01262170739157040.01408087420461-0.8963724274617950.370749427155152
44ar2_130.01537818231677110.01382174090331071.11260820357930.266738767793263
45ar2_14-0.02543720839540950.0132390760530926-1.921373386888840.0556013755600509
46ar2_150.01174187951671610.008208017226677011.430537874427660.15356988668656
47ar3_10.0002537688314948610.0003119720638117190.813434473568810.416593320568909
48ar3_2-0.000821934558611570.000384141726532477-2.13966487325110.033162430778026
49ar3_30.0003438074444142010.0003848909611844060.8932593359849760.372411219961082
50ar3_40.0003274911402466610.0003794137622564720.863150398918020.388722067903772
51ar3_5-1.43285464617726e-050.000381810622761658-0.03752788845457840.970088258745028
52ar3_60.0001806379297903950.000401669426408760.4497178971410390.653228152028532
53ar3_70.0001116873214529470.0004182707857976810.2670215689100750.789630099013966
54ar3_8-9.52164014763625e-050.000417067113421394-0.22829995080470.819563581091177
55ar3_90.0006249144132299820.0004211826307239331.483713637848440.138900895138677
56ar3_10-0.000721723569144850.000427238475743176-1.689275685878760.0921720534250932
57ar3_110.0002248529875683580.0004330104329353830.5192784525861810.603937110864321
58ar3_12-0.000422397053044310.000432497256825212-0.9766467795540630.329505562499354
59ar3_13-9.37300603802704e-050.000435408350499142-0.2152693219430.829698902723419
60ar3_140.0004783387596773990.0004209891448983461.136225875355770.256739644324555
61ar3_15-1.26202794907826e-050.000307070898978913-0.04109891081423910.967243499806413
62ar4_11.291056357700210.058365820460971922.12007554256041.00653959830003e-65
63ar4_2-0.4864632826782440.0938540691469453-5.183187975756273.94049900751884e-07
64ar4_30.1744329572741780.09734044642257491.791988466098960.074109943112255
65ar4_4-0.03115754398496050.0974465974169675-0.3197396811264680.7493810529357
66ar4_50.02026641588696520.0975351668810820.2077857303681520.8355327127096
67ar4_60.06686378613777320.09825588973482360.680506647675040.496691642351654
68ar4_7-0.103654525903870.0986475048679115-1.050756692150130.294188765523656
69ar4_80.1649144968404530.09811163127442531.680886299598620.0937922212688589
70ar4_9-0.1224406701700220.0987194311298361-1.240289462456360.215806277613451
71ar4_100.1047713556020260.09822093159365191.066690713497540.286941542976851
72ar4_11-0.1877459202286150.0979115289841147-1.917505754190350.0560924672566918
73ar4_120.1069574238160560.09841255889502511.086826976322660.277957613711121
74ar4_13-0.02271659979055580.0979529646705775-0.2319133460324890.816758333371353
75ar4_14-0.1131443453718650.0942545982420572-1.200411942569590.230895888776424
76ar4_150.0877835775757490.05616928584029571.562839481800450.119110593006932
77ar5_14.36416831753068e-052.2974706311924e-051.899553473406380.0584197182851223
78ar5_2-4.08826405273732e-052.96571570214403e-05-1.378508415281260.169040357497051
79ar5_3-4.08041845535584e-053.04946038481464e-05-1.338078853450610.181851403800572
80ar5_46.18084786806958e-053.04682091165881e-052.028621979197490.0433513210432282
81ar5_51.60513710516369e-053.07638150786648e-050.5217613943716880.602209053388486
82ar5_6-4.13483640254869e-053.23736635825305e-05-1.277222268035160.202479552074308
83ar5_7-5.17314998779717e-063.2447410165043e-05-0.1594318301979750.873432486336595
84ar5_81.12059068840126e-053.23052017844512e-050.3468762386559710.728919648880671
85ar5_93.39374309968384e-053.18359966371538e-051.066008122303670.287249499099693
86ar5_10-4.2496223141425e-053.1988943804627e-05-1.32846596627170.185001338904844
87ar5_111.56286524347765e-053.19322959191738e-050.4894309032565450.624882792445703
88ar5_12-3.30687846547516e-053.2077008300103e-05-1.030918605169470.303382625238005
89ar5_132.34980545358865e-053.22510324713872e-050.7285985202716760.46679732213478
90ar5_14-4.51842372226618e-053.22818461185427e-05-1.399679468662980.162609221807303
91ar5_154.85660163335178e-052.60930526729197e-051.861262342214230.0636535461124912
Rows: 1-91 | Columns: 5
Abc
predictor
Varchar(65000)
123
coefficient
Float
123
std_err
Float
123
t_value
Float
123
p_value
Float
1Intercept60.930919111298945.77425580744051.331117634497830.184128420798418
2ar0_1-0.1075963206757680.1137649279246-0.9457776015740030.344998623696202
3ar0_20.1758303518550970.1777774491716850.98904755734960.323411211468669
4ar0_3-0.00202109842409470.180390517374761-0.01120401700437430.991067881656568
5ar0_4-0.04332677873121330.180097254167992-0.2405743437420690.810044056817665
6ar0_5-0.006551847276710990.182405091283446-0.03591921272926440.971369894140936
7ar0_60.09737305696590730.1881910967676860.5174158535571440.605234894686378
8ar0_7-0.1967562336101880.185271970266111-1.061985972986530.289068672611273
9ar0_8-0.04190829735671290.182283799166171-0.229906868017980.818315767306276
10ar0_90.01172805369069250.1845491739061270.06354974905852520.949369702360853
11ar0_100.2797310520393380.1864923987884611.499959536456160.134642609524307
12ar0_11-0.1748730194163490.18493558639298-0.945588801090730.345094795676121
13ar0_120.04598288163103350.1844462162399750.2493023850985760.803291988078288
14ar0_13-0.1555986136658020.185026988170593-0.8409509077796890.401023623038031
15ar0_140.2290061991070050.1837890084309011.246027719841060.213695048755855
16ar0_15-0.07319719669172290.120241742076239-0.6087503010835650.543135769934925
17ar1_11.671749954571990.8712978058658711.918689503539670.0559417770028788
18ar1_2-1.761294507784211.40340016549757-1.255019452815690.210416979095048
19ar1_30.4228073488511651.426306113907690.2964352075115130.767096239627261
20ar1_4-1.850077907864261.43448121670793-1.289719158616880.19810952794892
21ar1_50.7574634860169451.4663258007150.5165724327073820.605822969062371
22ar1_61.119668342633531.463828619544770.7648903209596550.444918738890219
23ar1_7-3.697496022101181.43682421146548-2.573380927601390.0105356483434973
24ar1_83.765458543325051.431878487040912.629733303072860.00897151966688755
25ar1_9-0.03354809889526681.44653754079868-0.02319200017217930.981512040812113
26ar1_10-1.986533101608531.45059438087311-1.369461462006240.171846309376051
27ar1_11-0.6532067177972751.45704633191091-0.4483088172910720.654243508978995
28ar1_121.730125346288331.458910810523381.185902067356440.23656913885809
29ar1_13-0.4313428397695131.45479761104923-0.2964968023685580.767049251309346
30ar1_141.404330784079091.453481336307570.9661842563776270.334705125233138
31ar1_15-1.126918515157290.922126977968648-1.222086048973180.222603506114111
32ar2_1-19.647147269504826.4825352478658-0.7418907247971340.458715248340131
33ar2_22.8187018980097542.70213879855470.06600844775730880.947413648218357
34ar2_345.027785221500444.24814450436811.017619738089930.309652235184618
35ar2_4-66.610299287232945.2445251867421-1.472228938469480.141973556325614
36ar2_544.555392721653346.19849935289240.9644337661557350.335580227495996
37ar2_612.29625854222146.64212429210320.263629899556330.792240269597922
38ar2_7-41.678458712598546.4760201273299-0.8967734026797580.370535720205514
39ar2_8-8.6564273409749145.9486081872373-0.1883936789924210.850691320660986
40ar2_924.818785095230945.69858714722380.5430974269570730.587453003696965
41ar2_1018.463846298152945.66726647004260.4043124917552280.686261740572228
42ar2_11-9.1484113474689445.358555921049-0.2016909745405620.840290602872864
43ar2_12-24.166211048028344.9228930260902-0.5379486809541210.590998470407528
44ar2_1314.644072707163144.09616753983080.332094001002140.740042706458273
45ar2_1413.27279698415842.23726372774780.3142437699021320.753547275163463
46ar2_15-5.8111099123852926.1864337733802-0.2219129936773810.824527732788023
47ar3_10.9917193946080260.9952995422084030.9964029445925060.319831514851794
48ar3_2-0.3627923950652981.22554590269873-0.2960251380763510.767409087557136
49ar3_3-1.468569845147161.22793622219388-1.195965896765670.232623839540729
50ar3_41.539455643762721.210462049926821.271791745850920.204400390133655
51ar3_50.6055762282787781.21810886975550.497144584786030.619439495658271
52ar3_6-0.103905959676241.28146537013335-0.08108370471644280.935427707885052
53ar3_7-0.3950575306275821.33442948877252-0.296049760554210.767390301635651
54ar3_80.9004954166435831.330589354657790.6767643326555680.499060154198272
55ar3_9-1.149538732684051.34371928827146-0.8554902372226850.3929405206027
56ar3_100.08829459239984771.363039543109970.0647777189195780.948392733694057
57ar3_11-0.9304815340317421.38145409690321-0.6735522636022360.501097872330073
58ar3_121.438767420119631.379816886374541.042723447094480.297888867638332
59ar3_13-0.5043718471733881.38910428911691-0.3630914187832730.71678404873997
60ar3_140.8584298765845231.343102001097480.6391397495373240.523203995952804
61ar3_15-0.7004726058521560.979663119335222-0.7150137552666890.475138667126165
62ar4_1-58.221110597573186.207295857371-0.3126682567914450.754742943259079
63ar4_246.1706260014325299.4271695837710.1541965148507180.877555125966968
64ar4_3-20.8343084551743310.549927384592-0.06708843447698730.946554548761555
65ar4_4-21.1499133734033310.88858602868-0.06803052387215050.945805193756619
66ar4_5-403.761307173816311.171153467603-1.297553782458350.19540543196298
67ar4_6448.183559365716313.4705103959881.429747119751560.153796627374459
68ar4_7-353.715020120304314.719899068557-1.123904211863170.261923222275108
69ar4_8342.834401042841313.0102756626611.095281617566840.274243492350285
70ar4_9217.302984326321314.9493688957320.6899616439563720.490734496476501
71ar4_10-469.215005880862313.358981749867-1.497372129755660.135313934527955
72ar4_11372.325732616468312.3718796617251.191931018309550.234199953091241
73ar4_12-603.621162678726313.970339584287-1.922541993864620.0554537020119866
74ar4_13613.625707218249312.5040739334291.963576664760430.050472743922962
75ar4_14-105.862039759697300.704996899894-0.3520461610251810.725042839790013
76ar4_15-90.5178278622916179.199585373-0.5051229760039930.613831376426952
77ar5_10.9579321452374960.073297315135341713.06913006934432.15984940775476e-31
78ar5_2-0.1142728134093720.0946166603701312-1.207745157801460.228065903242638
79ar5_30.05500463945655550.09728840742677630.5653771185221070.572226237302043
80ar5_40.03018670931882640.09720419903992350.3105494373388970.756351861537123
81ar5_50.1131917249319660.0981472850173481.153284320722250.2496821422022
82ar5_6-0.05605170160558260.103283262448614-0.5426987904595840.587727154364312
83ar5_70.1639216164658710.1035185397324751.583500085004070.114327138767324
84ar5_8-0.07617799383422150.103064845467764-0.739126842799640.460389255393304
85ar5_9-0.04775024740604650.101567917625569-0.4701312040488820.63859184530846
86ar5_100.1173653821202830.1020558723607091.150011061641450.251025701428136
87ar5_11-0.2627295776179180.101875145875876-2.578936946387550.0103712687438826
88ar5_120.06481415796410770.1023368287737960.6333414738439080.52697763741737
89ar5_130.04408163191493490.1028920264921310.4284261221962260.668638431544053
90ar5_140.05459228121867450.1029903327588290.5300718985587930.596441534512659
91ar5_15-0.03693115810756350.0832459261347528-0.4436392244322190.657612920604488
Rows: 1-91 | Columns: 5

You can view other attributes using the 'getattr' method. In this case, we only have 'coef'

In [10]:
model.get_attr()
Out[10]:
attr_name
1coef
Rows: 1-1 | Column: attr_name | Type: undefined

Let's look at the SQL query for our model.

In [23]:
display(model.deploySQL())
'28.5362468915191 + 1.21249546311209 * ar0_1 + -0.265717276383384 * ar0_2 + 0.123604924076076 * ar0_3 ... + 0.0157764692081557 * ar5_12 + 0.0362569824401078 * ar5_13 + 0.0151394664766258 * ar5_14 + -0.0773020558834787 * ar5_1'

The best way to evaluate your model is with the regression report.

In [24]:
model.report()
Out[24]:
"Gold"
"Oil"
"Spread"
"Vix"
"Dol_Eur"
"SP500"
explained_variance-3.05626913151736-2.95236222736236-3.07643427955785-2.54947445633457-2.74605776244528-2.8912869164434
max_error3840.31462070037266.0886764526115.84729874087839131.0911199430612.273882203067676746.24885913539
median_absolute_error802.15998155475467.61756920245292.2112877714892639.46653870489831.594502535750792173.50932929945
mean_absolute_error1409.8932906900590.24592796299962.3855170727055743.14260031961811.617508986248122330.38823686522
mean_squared_error2884679.995721611443.57358987258.555936739346252123.905532264512.659713071522337627018.16755038
root_mean_squared_error1698.434572105031106.974639938036252.92505328829172846.085849588181731.6308626770891322761.705662729173
r20.99691789882970.9845053904373160.983333837059780.8092808254082770.9765251122598120.995213614862105
r2_adj0.99606439389023240.98021457548149580.97871859193787280.75646628475210750.97002437411637530.9938881543623802
Rows: 1-8 | Columns: 7

You can also add the prediction to your vDataFrame.

In [25]:
prediction = model.predict(commodities,
                           nlead = 5)
display(prediction)
📅
date
Timestamp
123
Gold
Float
123
Oil
Float
123
Spread
Float
123
Vix
Float
123
Dol_Eur
Float
123
SP500
Float
123
VAR_Gold
Float
123
VAR_Oil
Float
123
VAR_Spread
Float
123
VAR_Vix
Float
123
VAR_DolEur
Float
123
VAR_SP500
Float
11986-01-01 00:00:00345.56136363636422.92545454545451.0514285714285718.12136363636361.12159999999858211.779999[null][null][null][null][null][null]
21986-02-01 00:00:00339.052515.45473684210530.73684210526315820.62421052631581.07880000000296226.919998[null][null][null][null][null][null]
31986-03-01 00:00:00346.09473684210512.61250.56423.5641.04850000000442238.899994[null][null][null][null][null][null]
41986-04-01 00:00:00340.71590909090912.84363636363640.60409090909090923.01545454545451.05259999999544235.520004[null][null][null][null][null][null]
51986-05-01 00:00:00342.32515.3776190476190.64238095238095218.88751.03720000000612247.350006[null][null][null][null][null][null]
61986-06-01 00:00:00342.79761904761913.42571428571430.61476190476190518.59809523809521.0399999999936250.839996[null][null][null][null][null][null]
71986-07-01 00:00:00348.55434782608711.58454545454550.63681818181818219.63909090909091.01029999999446236.119995[null][null][null][null][null][null]
81986-08-01 00:00:00376.2915.09666666666670.8395238095238118.63809523809520.979300000000876252.929993[null][null][null][null][null][null]
91986-09-01 00:00:00418.15227272727314.86666666666671.1014285714285722.70523809523810.973200000000361231.320007[null][null][null][null][null][null]
101986-10-01 00:00:00423.86304347826114.89681818181821.1472727272727322.52391304347830.961600000000544243.979996[null][null][null][null][null][null]
111986-11-01 00:00:00396.982515.22157894736840.97388888888888918.63157894736840.967399999999543249.220001[null][null][null][null][null][null]
121986-12-01 00:00:00391.59523809523816.1076190476190.84090909090909119.75863636363640.957399999999325242.169998[null][null][null][null][null][null]
131987-01-01 00:00:00408.5238095238118.65142857142860.858520.76666666666670.900400000000445274.079987[null][null][null][null][null][null]
141987-02-01 00:00:00401.04517.74894736842110.85263157894736823.44631578947370.882600000000821284.200012[null][null][null][null][null][null]
151987-03-01 00:00:00408.84772727272718.30285714285710.82409090909090921.83727272727270.883599999999206291.700012[null][null][null][null][null][null]
161987-04-01 00:00:00439.66518.67714285714290.99857142857142926.88142857142860.872100000000501288.359985411.355044065918.50842855271210.91031440980681824.94010344739570.880950608126736235.236679270353
171987-05-01 00:00:00461.6519.43750.851525.41150.861100000000079290.100006424.96007906386617.51684766092841.1105455559766828.58054445692270.873784687026657267.899010686334
181987-06-01 00:00:00449.27727272727320.07318181818180.82909090909090921.62454545454550.876500000000306304.0461.03103431822519.64877702812730.73146937630245323.73408900511440.856760492118254318.283163761874
191987-07-01 00:00:00450.33043478260921.34217391304351.0045454545454517.80090909090910.888600000000224318.660004437.32803264068821.42828166614690.90259595506050822.37460340770840.876091462782457336.669491113972
201987-08-01 00:00:00460.987520.31095238095241.0076190476190520.84904761904760.89600000000064329.799988454.87168857223623.99843766534331.018529226448216.72209459967350.882473841168488333.750504275913
211987-09-01 00:00:00460.12045454545519.531.0780952380952422.89380952380950.873499999999694321.829987444.07493873651321.35075669024661.0499190343534321.90140359304520.891336691703758327.391054952531
221987-10-01 00:00:00465.76363636363619.85909090909091.1223809523809558.21954545454550.868599999999788251.789993454.94261978832621.17652671360391.1303459933077927.30130842910180.855049638827143334.191514175582
231987-11-01 00:00:00468.14047619047618.8541.1678947368421149.43650.814700000000812230.300003469.02997361428118.8524143736541.1137814078014148.14802048249510.861856395605669275.080495687973
241987-12-01 00:00:00487.07857142857117.27454545454551.1341.76409090909090.791400000000067247.080002476.15336671229219.09869799740031.0832950612936842.03678617814780.775765573263347251.733960399326
251988-01-01 00:00:00477.757517.12951.0357894736842138.33650.800100000000384257.070007495.99803216084917.4963786081061.1291823993570337.41173616894340.794839728955063225.203958494543
261988-02-01 00:00:00442.1238095238116.79571428571431.031533.6740.822000000000116267.820007477.33568492841316.5184966510070.99859709019751432.60023043194030.809815322427057299.136252546634
271988-03-01 00:00:00443.49130434782616.19739130434781.1030434782608729.35695652173910.810900000000402258.890015452.57509122688618.30025348721381.1077869723964433.72176627314490.828922926591218316.018563607931
281988-04-01 00:00:00451.55789473684217.86251.12927.4050.805700000000798261.329987440.83058531788420.36089972379661.1492811528583927.87320898966680.8131264604025318.681422294923
291988-05-01 00:00:00451.3217.42363636363641.0933333333333325.71666666666670.813099999999395262.160004425.6572233699416.06488918470931.24268978310527.46646513705650.814103982467299280.013363981091
301988-06-01 00:00:00451.65681818181816.52772727272730.89545454545454625.27090909090910.842500000000655273.5451.89081893579721.46990868569881.0149440948448425.92258993595260.823002192924385308.468259105851
311988-07-01 00:00:00437.45238095238115.49750.77723.6440.886300000000119272.019989413.41486080498814.74714247163780.85271079631159524.99804285627210.871149106780759263.627212859389
321988-08-01 00:00:00431.06363636363615.52347826086960.63173913043478323.70739130434780.905899999999747261.519989434.51598382637317.74619791334110.66259540710220426.47055883154870.88823791097993243.579433636489
331988-09-01 00:00:00413.43863636363614.53545454545450.51380952380952419.52428571428570.900299999999334271.910004437.56785139938814.99910857095310.59877832422622223.81766592554050.891551715460677260.366762885071
341988-10-01 00:00:00406.39047619047613.77047619047620.441520.48190476190480.87960000000021278.970001429.03148308654113.77775798623390.51845329588017219.26888876916620.88435871261458333.588818935755
351988-11-01 00:00:00419.96590909090914.14136363636360.296521.65904761904760.844499999999243273.700012439.26656624688412.70412865504450.44755609620121421.71426291133520.866210924002418293.434089362222
361988-12-01 00:00:00419.247516.3823809523810.017142857142857117.75428571428570.843999999999141277.720001421.073703827811.92246431230360.20975858145258421.80890247888980.847852058295543286.98233734469
371989-01-01 00:00:00404.44523809523818.0242857142857-0.08417.75809523809520.880499999999302297.470001396.30371514819417.8664402428583-0.02427538015164119.43365432961520.864370896081727277.668488628309
381989-02-01 00:00:00387.972517.9365-0.20263157894736818.31263157894740.888899999999921288.859985380.3482846609418.7446878599506-0.071868125928565416.17770547279890.90662757731756307.005847936643
391989-03-01 00:00:00390.2738095238119.4840909090909-0.32181818181818217.47545454545450.896699999999328294.869995359.13128257489516.8923580991221-0.20663749610920717.55074458332010.897132807053984324.809780005387
401989-04-01 00:00:00384.7221.069-0.27616.88750.899199999999837309.640015384.75178861224820.9473210216838-0.35980214967252616.33157269341380.899515333960255345.812429988646
411989-05-01 00:00:00371.3520.1234782608696-0.15863636363636417.4350.9375320.519989364.93414664939821.6841648171812-0.26181342630099817.53804890410070.903079854051664312.696008320321
421989-06-01 00:00:00367.72727272727320.0504545454545-0.12909090909090916.73227272727270.955400000000736317.980011343.8853447795220.0355697856499-0.13374962351028817.82398221198280.944983538745869313.796588543701
431989-07-01 00:00:00375.20952380952419.78142857142860.19918.05650.914000000000669346.079987350.46422326211821.0398060855966-0.051330143519786118.79849206027560.947398856147633306.396366701819
441989-08-01 00:00:00365.54772727272718.5778260869565-0.032173913043478319.32347826086960.927799999999479351.450012378.74580492598620.17534714314670.29750738258437519.51433971585820.897251412260211334.564185721183
451989-09-01 00:00:00361.79761904761919.5914285714286-0.09416.74650.941100000000006349.149994375.74222994207619.4460240568004-0.20128489006778416.66556503805590.933844074957064368.645851073038
461989-10-01 00:00:00366.820.09772727272730.028571428571428621.95090909090910.907199999999648340.359985352.26054887519920.91630996511790.036696768862870116.35999380520390.934267443802669363.175631270713
471989-11-01 00:00:00394.36136363636419.85590909090910.078571428571428620.9323809523810.893899999999121345.98999364.62636004144121.04996590116750.063710306121114821.83778628030680.897145405631703323.786469208829
481989-12-01 00:00:00409.65526315789521.10.05918.2350.856499999999869353.399994389.03750343104621.15158517477890.070341124386881618.32611594827940.883477418538363364.237554044389
491990-01-01 00:00:00410.11818181818222.86318181818180.12142857142857123.49909090909090.831899999999223329.079987401.65594485265322.2175979483140.15511984742649320.11187491945430.847746279250939335.887230559454
501990-02-01 00:00:00416.542522.1130.10263157894736823.32684210526320.820799999999508331.890015405.65977439227724.32528500596760.22067021963929621.9218755637380.831641600618811351.520691459941
511990-03-01 00:00:00393.66136363636420.3877272727273-0.038181818181818218.83136363636360.835100000000239339.940002409.89930561725223.66450383944770.12382693214303522.90764058143080.815719498817479358.123802415358
521990-04-01 00:00:00374.92894736842118.42550.061520.45750.82510000000002330.799988373.2011816610921.7397264219633-0.0035138481811234120.28175902626730.842171627253246340.318415409981
531990-05-01 00:00:00368.85476190476218.19954545454550.11590909090909118.15181818181820.811400000000504361.230011369.9081452510517.69577469249920.18500910031048920.12352412713880.823327264851873362.105785613393
541990-06-01 00:00:00352.65714285714316.69523809523810.12904761904761917.58285714285710.817699999999604358.019989371.1045281211519.28387006309990.11376495789309819.71180697957960.808977941851329366.397234319787
551990-07-01 00:00:00361.82045454545518.45409090909090.31428571428571418.93285714285710.792699999999968356.149994329.29334598655416.78009395028250.27612113634289321.64706367209520.819780197725696372.74848188527
561990-08-01 00:00:00394.86136363636427.30739130434780.69130434782608727.77521739130430.759899999999106322.559998369.5952099206919.44252395124160.39573225360341122.64022013277450.780286097369445337.812296730001
571990-09-01 00:00:00389.5633.50750.81368421052631628.81894736842110.761699999999109306.049988398.71976111537928.55487393009530.82944545326846326.78548548017380.745202886277533334.068469388899
581990-10-01 00:00:00381.33260869565236.03956521739130.84181818181818230.13043478260870.739799999999377304.0387.76700151891636.93609605377210.81987580952409524.89221587178120.754211340967542364.722868660082
591990-11-01 00:00:00381.86590909090932.33227272727270.793525.10666666666670.72400000000016322.220001387.41970959286937.30016886897020.94192025262979927.55817914391540.718888780749374313.842883860227
601990-12-01 00:00:00378.16052631578927.2810.76122.58450.731999999999971330.220001390.53261948163932.80441315993970.81357958286939923.57049440219920.712977227680873338.909388173528
611991-01-01 00:00:00384.59090909090925.23409090909090.96761904761904826.93181818181820.736699999999473343.929993374.94079468239526.42476244637840.83360123980268224.12739939072420.730245257414686336.968785479775
621991-02-01 00:00:00363.747520.47750.98789473684210522.11263157894740.722599999999147367.070007375.53149537322624.44662923085341.0774822467456627.14148105134780.742028064957961368.327084624538
631991-03-01 00:00:00363.3919.90151.00719.04105263157890.781800000000658375.220001359.7191495708818.3969955790710.9608738254870621.91042436103040.729223174815362355.428667219016
641991-04-01 00:00:00358.05476190476220.831.0909090909090918.92727272727270.826699999999619375.339996355.85058872875320.45797667058431.0903789777925222.93636942507670.816454144474601355.418534327117
651991-05-01 00:00:00357.11666666666721.23227272727271.2840909090909117.18045454545450.83389999999963389.829987341.34781839233319.99833774592381.1008538131427119.54542031993740.850615536432393368.604684535449
661991-06-01 00:00:00366.3620.1891.32817.5750.868700000000899371.160004365.65784970629921.7472627066371.2578245861494916.28720487871820.835083846086506408.616646649566
671991-07-01 00:00:00368.01304347826121.40304347826091.35517.66954545454550.870699999999488387.809998365.2468239285120.31473498559391.3408049150863418.45425743460840.875149143891069361.927937518342
681991-08-01 00:00:00356.72142857142921.69363636363641.4668181818181815.93272727272730.850300000000061395.429993370.94296719469323.54061415841731.4622342936877621.10609358190780.848057198173779350.604288860519
691991-09-01 00:00:00348.45952380952421.88651.468517.0290.828100000000632387.859985367.62230170927820.62163188533851.5023300508404519.27518626672060.846431764932451375.797007007506
701991-10-01 00:00:00358.82608695652223.23086956521741.61516.84636363636360.82550000000083392.450012327.8408785675621.85066112127841.4771302201431918.07871030496520.819874252202833405.006310293107
711991-11-01 00:00:00359.95952380952422.46095238095241.8584210526315817.68150.795000000000073375.220001368.27618188850721.65166192993331.67388105352418.26579617577790.824081196146417389.503947348051
721991-12-01 00:00:00361.87519.49809523809522.0628571428571418.01857142857140.768099999999322417.089996365.74046222775720.68245749912741.8752609831440217.64848292443020.795204138192015385.350968469591
731992-01-01 00:00:00354.43636363636418.78545454545452.0742857142857117.49954545454550.770599999999831408.779999355.9110455990418.66716689223042.1015170400260217.59971022301790.775430756400955411.8373684889
741992-02-01 00:00:00353.852519.01252.1257894736842117.05052631578950.791999999999462412.700012366.38607755869719.74081961502692.0787377211203419.9999601664080.77871535355255407.381762257794
751992-03-01 00:00:00344.64090909090918.92181818181821.8572727272727316.22272727272730.812700000000404403.690002369.45986021839819.78860522231832.1079973136188116.3901154096630.795083877741216412.906112529731
761992-04-01 00:00:00338.727520.232.1361904761904816.18857142857140.804899999999179414.950012328.76978562684219.0670433995191.8083441649088216.17400483380480.827798421681564406.627500658726
771992-05-01 00:00:00337.03947368421120.97552.166514.7280.78859999999986415.350006346.76933041574522.71525830243462.2861684165157415.08658404001980.78575859635025449.985406235885
781992-06-01 00:00:00340.78409090909122.38454545454552.2136363636363614.75318181818180.767900000000736408.140015356.84538617063721.29224306516372.0970299911401416.24990730419040.77782335453544390.469668857413
791992-07-01 00:00:00352.45217391304321.77521739130432.4890909090909113.30363636363640.729799999999159424.209991334.55664449933922.80355695608232.3446589200012216.28075974741050.751931553184405434.279626197446
801992-08-01 00:00:00343.602521.33904761904762.3928571428571414.4223809523810.71349999999984414.029999371.9185772287721.43184654931352.5216829290474116.98371280483710.722698252023182392.216276536992
811992-09-01 00:00:00345.321.88136363636362.5209523809523814.25857142857140.721999999999753417.799988346.39156952472522.15054057755432.272971907273415.19208009121720.708862241310508414.042065831439
821992-10-01 00:00:00344.27727272727321.68590909090912.5061904761904817.47863636363640.755199999999604418.679993345.36553865615720.62265937194142.582862473432514.43799328148010.734351075712842449.683350708215
831992-11-01 00:00:00334.92380952380920.33852.2936842105263214.5940.807199999999284431.350006345.0731998562822.03508878670022.363345465648315.3288305978050.77230935732692425.738496866752
841992-12-01 00:00:00334.65714285714319.41409090909092.0963636363636412.78136363636360.807199999999284435.709991333.80084902292719.22086755360292.15300311593112.40511079478270.808269215972854471.391993513972
851993-01-01 00:00:00328.992519.0322.2112.5840.825000000000728438.779999333.66263488176519.83253052820522.0484251236945314.95150272408940.800928526411801423.913559899936
861993-02-01 00:00:00329.3120.08611111111112.1605263157894713.62473684210530.845300000000861443.380005330.14921704619819.54866647293852.1919151235362112.22324786280290.821478466378602436.082000790029
871993-03-01 00:00:00329.97391304347820.32217391304352.0256521739130413.69304347826090.848400000000766451.670013319.43126803835718.64599998810852.1052319538657714.45173743515560.852305413645222432.986187861282
881993-04-01 00:00:00341.947520.25252.1319047619047613.45666666666670.820100000000821440.190002336.4823781242921.19980831665022.0077439117659613.87717529911380.837087699372448440.53354264787
891993-05-01 00:00:00367.04473684210519.94952.058513.48550.821200000000317450.190002362.59748354938619.0075141292.0583543926297314.46373045545960.820896126133905426.511014947833
901993-06-01 00:00:00371.91363636363619.09409090909091.7990909090909112.97318181818180.844300000000658450.529999372.54941901916519.41165852852871.8993511469204812.82222148036270.826128883568956440.953820158298
911993-07-01 00:00:00392.03409090909117.891.7333333333333311.86950.878399999999601448.130005352.2207044615317.57771138102941.7293370960153411.57524490676180.861588760458517484.423165147856
921993-08-01 00:00:00379.79523809523818.01090909090911.6763636363636411.95318181818180.882400000000416463.559998402.97836844195319.08304815375331.5937259337640411.63289951984090.889367996664907453.185076076181
931993-09-01 00:00:00355.56136363636417.50428571428571.5128571428571412.6490.848200000000361458.929993365.7204456675718.04137138584881.5540700545148911.03443946765670.874102732514991450.66087817258
941993-10-01 00:00:00364.00476190476218.15333333333331.459511.37523809523810.859300000000076467.829987347.07342405157219.18122518708941.4393598000726612.09008547826160.838959364160882488.741575559702
951993-11-01 00:00:00373.93863636363616.60904761904761.568513.37095238095240.885800000000018461.790009376.39052057478519.26389064938041.4381093928560110.91772475438960.86935761286495465.6074284475
961993-12-01 00:00:00383.24285714285714.51476190476191.5618181818181810.86454545454550.885800000000018466.450012372.62969374774214.58459066177071.5306023169530113.52362216708920.890047368784371450.164220288289
971994-01-01 00:00:00387.1115.02666666666671.610510.60523809523810.897499999999127481.609985389.57688248599813.55902707746951.4764300436808811.76913878919690.877024057312378448.984566013094
981994-02-01 00:00:00381.657514.78105263157891.4989473684210512.88526315789470.894800000000032467.140015393.15105089064417.19039764289291.5850386604037911.35532624593790.902345991167799487.919025299086
991994-03-01 00:00:00384.014.68086956521741.4873913043478314.24086956521740.876000000000204445.769989383.97034699721213.96911542553241.4037754604442512.42380850094210.889025963348885473.431997689685
1001994-04-01 00:00:00377.90789473684216.421.4226315789473715.33473684210530.877300000000105450.910004388.59881338677314.89498927854931.4703890434195812.84075440229090.859678565955822485.344000937376
Rows: 1-100 | Columns: 13

The vDataFrame has the 'score' method to evaluate the quality of your model.

In [26]:
prediction.score("Gold", "VAR_Gold", method = "mse")
Out[26]:
692.670582020292

Let's examine our prediction with a boxplot.

In [27]:
prediction.boxplot(["Gold", "VAR_Gold"])
Out[27]:
<AxesSubplot:>

You can also check the importance of each feature.

In [28]:
model.features_importance(X_idx = 'Gold')
Out[28]:
importance
sign
ar0_117.738617512794371
ar0_23.887401871350819-1
ar0_31.80832055672673891
ar0_41.2384677071116508-1
ar0_52.1591937253399521
ar0_61.0924655019460674-1
ar0_70.43947827381923121
ar0_84.134330805838118-1
ar0_93.09371302930677231
ar0_100.42380041582799277-1
ar0_112.22993694237354531
ar0_122.354476897102296-1
ar0_131.2679767058746431
ar0_140.413730073298678561
ar0_151.559166259572152-1
ar1_10.194768887087744621
ar1_20.40121712446854396-1
ar1_31.2893096473919512-1
ar1_42.2705440138812131
ar1_50.9379032028108268-1
ar1_60.7549009772482425-1
ar1_70.76228364672617771
ar1_80.68271704234937441
ar1_91.4450091797891484-1
ar1_101.48563358713391
ar1_110.5079803719504629-1
ar1_120.8357446076122496-1
ar1_130.71818701402936161
ar1_140.8234621601464627-1
ar1_150.74848397675789371
ar2_10.07737908405504616-1
ar2_20.356267824662327371
ar2_30.1569168213727553-1
ar2_40.6698582812725141
ar2_51.2338265044047911-1
ar2_60.47652670749845591
ar2_70.50788062674876781
ar2_80.28629279186839446-1
ar2_90.524422987149711-1
ar2_100.19775496830383071
ar2_110.245670455303163171
ar2_120.08044388196657389-1
ar2_130.14665959281794846-1
ar2_140.08976867635790785-1
ar2_150.23000456386423751
ar3_10.24628835637709276-1
ar3_20.5506904998580871
ar3_30.031310673846336331
ar3_40.3946021399575358-1
ar3_50.29839696020449191
ar3_60.02181685061059711-1
ar3_70.5752777023542656-1
ar3_80.344126232681972841
ar3_90.4165534161580779-1
ar3_100.60845260894975671
ar3_110.13768019213888064-1
ar3_120.119484121965832081
ar3_130.53316547384263211
ar3_140.40028229202730675-1
ar3_150.15537010767613696-1
ar4_10.21352336200590968-1
ar4_20.42589460211565267-1
ar4_31.07431840658444561
ar4_40.641840532427105-1
ar4_50.14821329619255781
ar4_60.07162906380286331-1
ar4_70.5172393354265551
ar4_80.7880522260935021-1
ar4_90.379259048775448471
ar4_100.5706926612319556-1
ar4_110.373898682425829851
ar4_120.40343962398296641
ar4_130.9131941445928474-1
ar4_141.64186362106980251
ar4_151.111136166884665-1
ar5_11.8061390868121736-1
ar5_22.67545353189263931
ar5_32.494794435642391
ar5_42.1676961543010806-1
ar5_52.084168877734961-1
ar5_61.26189486025489631
ar5_71.3158655886250212-1
ar5_81.2660294087227613-1
ar5_90.46065128105866921
ar5_102.847456489946941
ar5_110.48025883634034666-1
ar5_120.4425824356157441
ar5_131.0171289522832381
ar5_140.42471239025295511
ar5_152.1685797829420586-1
Rows: 1-90 | Columns: 3

Let's visualize our model with a graph.

In [29]:
for elem in ['Gold', 
             'Oil', 
             'Spread', 
             'Vix', 
             'Dol_Eur', 
             'SP500']:
    model.plot(X_idx = elem,
               dynamic = True,
               nlead = 100)