Multiple Linear Regression - Estimated Regression Equation
Yt[t] = + 17424.9461206477 -0.0769106839892755`Yt-1`[t] + 0.289791286320848`Yt-2`[t] -0.229658583665953`Yt-3`[t] -0.248195965086348`Yt-4`[t] -482.673839824678M1[t] + 682.241579160312M2[t] -52.7929730074228M3[t] + 704.745486669194M4[t] + 478.005060254843M5[t] -46.9907665014013M6[t] + 655.375475998909M7[t] + 604.825547340014M8[t] -1081.26087721467M9[t] + 581.745707803682M10[t] + 738.588003595692M11[t] -155.411865696257t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)17424.94612064774246.5864024.10330.0002011e-04
`Yt-1`-0.07691068398927550.15908-0.48350.6314640.315732
`Yt-2`0.2897912863208480.157531.83960.0734480.036724
`Yt-3`-0.2296585836659530.153446-1.49670.1425290.071264
`Yt-4`-0.2481959650863480.154441-1.60710.116110.058055
M1-482.6738398246781029.309839-0.46890.6417310.320865
M2682.2415791603121012.5249680.67380.5044110.252206
M3-52.79297300742281017.625576-0.05190.958890.479445
M4704.7454866691941009.2091350.69830.4891240.244562
M5478.0050602548431029.1948850.46440.6449110.322455
M6-46.99076650140131006.65-0.04670.9630060.481503
M7655.3754759989091037.0915210.63190.5311160.265558
M8604.8255473400141024.9842160.59010.5585390.279269
M9-1081.260877214671068.706898-1.01170.3178950.158948
M10581.7457078036821106.0054170.5260.6018750.300937
M11738.5880035956921086.0667720.68010.5004850.250243
t-155.41186569625739.28188-3.95630.0003120.000156


Multiple Linear Regression - Regression Statistics
Multiple R0.866131590033882
R-squared0.75018393125462
Adjusted R-squared0.647695287666772
F-TEST (value)7.31967860040609
F-TEST (DF numerator)16
F-TEST (DF denominator)39
p-value2.06504179978140e-07
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1472.27954328209
Sum Squared Residuals84536675.0891104


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
115335.6363613947.78871231811387.84764768191
211188.514509.2671097938-3320.7671097938
313633.2514126.9903575724-493.740357572352
412298.4666712743.4322415577-444.965571557676
515353.6363613755.02729311601598.60906688404
612696.1538512920.6805207395-224.526670739477
712213.9333314257.1526128946-2043.21928289462
813683.7272712947.8053465242735.921923475761
911214.1428610705.5537738950508.589086104975
1013950.2307713599.3419137661350.888856233935
1111179.1333312456.8083012018-1277.67497120176
1211801.87512771.1941987747-969.319198774715
1311188.8235311266.7479256135-77.9243956134569
1416456.2727312461.18713026263995.08559973738
1511110.062511532.7178510228-422.655351022818
1616530.6923114058.71657237012471.97573762993
1710038.4117610652.8167728662-614.405012866218
1811681.2511963.0295351384-281.77953513844
1911148.8823510584.2394103273564.642939672658
20863111040.9320916604-2409.93209166037
219386.44444410472.8762823912-1086.43183839125
229764.73684210907.2258658294-1142.48902382937
2312043.7511808.8675830287234.882416971303
2412948.0666711300.6470323411647.41963765900
2510987.12510979.07150860248.0534913975518
2611648.312511784.1699372059-135.857437205851
2710633.352949501.281371710241132.07156828976
2810219.310598.9749137253-379.67491372535
299037.610289.3917054579-1251.79170545792
3010296.315799648.8705395503647.445250449693
3111705.4117610103.56954023301601.84221976705
3210681.9444410528.1518962732153.792543726773
339362.9473689177.93119771314185.016170286857
3411306.352949854.359807864391451.99313213561
3510984.459209.40384896691775.04615103311
3610062.619059460.28321415828602.335835841715
378118.5833338680.86147054834-562.278137548336
388867.489164.32591554183-296.84591554183
398346.727944.51813291235402.201867087648
408529.3076929478.97967478225-949.671982782253
4110697.181829242.384001215231454.79781878477
428591.848381.8798219205209.960178079504
438695.6071439806.3062103056-1110.69906730559
448125.5714298439.06546961245-313.494040612452
457009.7586216616.93203900059392.826581999415
467883.4666678543.85963154018-660.392964540184
477527.6451618259.89875780266-732.253596802657
486763.7586218044.194895726-1280.43627472600
496682.3333337438.03193891767-755.698605917668
507855.6818188097.29695519589-241.615137195890
516738.887356.75772678224-617.877726782237
527895.4347838593.09805256466-697.663269564656
536361.8846157549.09478234467-1187.21016734467
546935.9565227287.05574465128-351.099222651279
558344.4545457357.0213542395987.433190760505
569107.9444447274.232778929711833.71166507029


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
200.976128784289260.04774243142147790.0238712157107390
210.9996209033675330.0007581932649340880.000379096632467044
220.9997377896507860.0005244206984275470.000262210349213774
230.999159829282480.001680341435039550.000840170717519775
240.9984729409663780.003054118067244050.00152705903362203
250.996044984852830.00791003029433980.0039550151471699
260.9913367823436260.01732643531274790.00866321765637397
270.9833905713126520.03321885737469520.0166094286873476
280.970572542115880.05885491576824040.0294274578841202
290.9739595121242250.05208097575154990.0260404878757749
300.9488957578022780.1022084843954450.0511042421977225
310.9150547026551650.1698905946896700.0849452973448348
320.872947803814960.2541043923700810.127052196185040
330.7881298863280930.4237402273438130.211870113671907
340.7642061982615040.4715876034769920.235793801738496
350.6853562441090530.6292875117818940.314643755890947
360.6034963697936140.7930072604127730.396503630206386


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level50.294117647058824NOK
5% type I error level80.470588235294118NOK
10% type I error level100.588235294117647NOK