Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 3.46094894308918 -1.35890812535706X[t] + 1.57594470852792Y1[t] -0.641364831745757Y2[t] + 0.301634497468656M1[t] + 0.112538207357399M2[t] + 0.0715051759643893M3[t] + 0.263299441206298M4[t] + 0.460167495643472M5[t] + 0.100278611311066M6[t] + 0.184482326076706M7[t] + 0.262352168000846M8[t] + 0.194356140873652M9[t] + 0.104842003651204M10[t] + 0.00988454894042862M11[t] -0.0031959243864679t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)3.460948943089181.3934262.48380.0169750.008488
X-1.358908125357060.527899-2.57420.0135760.006788
Y11.575944708527920.10681114.754500
Y2-0.6413648317457570.104974-6.109800
M10.3016344974686560.5390820.55950.5787010.28935
M20.1125382073573990.5389150.20880.8355720.417786
M30.07150517596438930.5387470.13270.895030.447515
M40.2632994412062980.5388750.48860.6276010.3138
M50.4601674956434720.5464630.84210.4044010.2022
M60.1002786113110660.5457360.18370.8550740.427537
M70.1844823260767060.5404790.34130.7345170.367258
M80.2623521680008460.5390490.48670.6289470.314473
M90.1943561408736520.5389810.36060.7201650.360082
M100.1048420036512040.5388550.19460.846650.423325
M110.009884548940428620.5389310.01830.9854520.492726
t-0.00319592438646790.016433-0.19450.8467130.423356


Multiple Linear Regression - Regression Statistics
Multiple R0.997691270248974
R-squared0.995387870731012
Adjusted R-squared0.993778988427876
F-TEST (value)618.682838882126
F-TEST (DF numerator)15
F-TEST (DF denominator)43
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.801038532138557
Sum Squared Residuals27.5914973887398


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
154.855.7110417169253-0.911041716925267
252.754.0124347512415-1.31243475124146
350.951.4283597056483-0.528359705648272
450.650.12712371781950.472876282180463
552.151.00246913245421.09753086754576
653.353.1957108360510.104289163949020
753.954.205805029045-0.305805029045017
854.354.4564079736045-0.156407973604542
954.254.6307750064546-0.430775006454585
1054.254.12392454129460.076075458705416
1153.554.0899076453719-0.589907645371917
1251.452.9736658760755-1.57366587607547
1350.550.4115759434710.0884240565289558
1450.350.14779963796430.152200362035715
1549.850.3656100890504-0.565610089050398
1650.749.8945090419910.805490958008976
1752.851.82721382558980.972786174410244
1855.354.19638455620831.10361544379167
1957.356.87038797124120.429612028758775
2057.558.4935392264703-0.99353922647035
2156.857.4548065531708-0.654806553170764
2256.456.13066222924310.269337770756858
2356.355.85108634895680.448913651043235
2456.455.93695733747540.463042662524625
255756.45712686458490.542873135415067
2657.957.14626499202940.75373500797061
2758.958.13556737487760.764432625122414
2858.859.3228820756898-0.522882075689771
2956.557.3586867777849-0.858686777784864
3051.953.4350656226264-1.53506562262635
3147.447.7418668667923-0.341866866792309
3244.943.67506782198481.22493217801519
3343.942.55015584200721.34984415799276
3443.442.48491315123480.915086848765203
3542.942.24015224961930.65984775038065
3642.641.75978183790140.840218162098634
3742.241.90611941429810.293880585701941
3841.241.2758587659129-0.0758587659128922
3940.239.91223103430380.287768965696208
4039.339.16624949837710.133750501622929
4138.538.5829362224984-0.0829362224983919
4238.337.53632399552840.763676004471629
4337.937.81523470959860.0847652904014438
4437.637.38780371007420.212196289925788
4537.337.10037427870050.199625721299517
463636.7272902540569-0.727290254056906
4734.534.7728182033971-0.272818203397096
4833.533.22959494854780.270405051452204
4932.932.9141360607207-0.0141360607206959
5032.932.41764185285200.482358147148027
5132.832.75823179612000.0417682038800483
5231.932.7892356661226-0.889235666122597
5330.531.6286940416727-1.12869404167275
5429.229.636514989586-0.436514989585965
5528.728.56670542332290.133294576677107
5628.428.6871812678661-0.287181267866087
572828.4638883196669-0.463888319666924
5827.427.9332098241706-0.533209824170572
5926.927.1460355526549-0.246035552654873


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
190.3837977048946200.7675954097892410.61620229510538
200.5680139897458880.8639720205082240.431986010254112
210.68157814113010.63684371773980.3184218588699
220.5862692512411310.8274614975177380.413730748758869
230.638525697685490.7229486046290190.361474302314510
240.947946809830370.1041063803392590.0520531901696295
250.926808318727810.146383362544380.07319168127219
260.9115659738191780.1768680523616440.0884340261808222
270.8879158984992980.2241682030014030.112084101500702
280.9462478258012610.1075043483974770.0537521741987387
290.9968806168045020.006238766390995150.00311938319549758
300.9962502614134070.007499477173185050.00374973858659253
310.9922029236610930.01559415267781410.00779707633890706
320.9968096116156540.006380776768692910.00319038838434646
330.9956745687739170.008650862452165010.00432543122608251
340.991440854360570.01711829127886130.00855914563943065
350.9867012739142090.02659745217158260.0132987260857913
360.970416152094340.05916769581132130.0295838479056607
370.946540854667740.1069182906645190.0534591453322594
380.9486931436223740.1026137127552520.0513068563776259
390.89537865985970.2092426802806000.104621340140300
400.7982171314032750.4035657371934490.201782868596725


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.181818181818182NOK
5% type I error level70.318181818181818NOK
10% type I error level80.363636363636364NOK