Multiple Linear Regression - Estimated Regression Equation
y[t] = -40.2944805912345 + 0.0638539628062868x[t] + 0.682999055030689y1[t] + 0.122458369917985y2[t] + 0.218214695228774y3[t] + 3.70568054851267M1[t] + 2.87391682631078M2[t] + 1.61334266086646M3[t] + 1.73017385141576M4[t] + 0.646074597671226M5[t] + 2.809494330732M6[t] + 1.90389388989760M7[t] + 0.793880895008001M8[t] -1.33056690921134M9[t] -0.0375894807118368M10[t] -2.25856294729839M11[t] + 0.107006757579222t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)-40.294480591234515.29372-2.63470.011830.005915
x0.06385396280628680.0231472.75860.0086340.004317
y10.6829990550306890.1499174.55584.6e-052.3e-05
y20.1224583699179850.1851720.66130.5121050.256052
y30.2182146952287740.1599791.3640.1800030.090002
M13.705680548512672.2196161.66950.1026350.051317
M22.873916826310782.3107061.24370.220660.11033
M31.613342660866462.2457810.71840.4765920.238296
M41.730173851415762.1657720.79890.4289680.214484
M50.6460745976712262.1898380.2950.7694570.384729
M62.8094943307322.1867991.28480.206090.103045
M71.903893889897602.2363670.85130.3995290.199765
M80.7938808950080012.3030070.34470.7320710.366035
M9-1.330566909211342.444624-0.54430.5891950.294597
M10-0.03758948071183682.300216-0.01630.9870410.493521
M11-2.258562947298392.326337-0.97090.3373080.168654
t0.1070067575792220.0577181.8540.0709480.035474


Multiple Linear Regression - Regression Statistics
Multiple R0.931011076253719
R-squared0.866781624107108
Adjusted R-squared0.814793965222077
F-TEST (value)16.6728343360097
F-TEST (DF numerator)16
F-TEST (DF denominator)41
p-value4.49307258065801e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.16773018165331
Sum Squared Residuals411.415094654049


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
11920.8386264980515-1.83862649805149
22219.7626973568932.23730264310701
32320.74863388373622.25136611626385
42021.7035761826179-1.70357618261788
51418.7521953860957-4.75219538609566
61416.3923433551886-2.39234335518862
71414.3320632923518-0.332063292351784
81515.3401749495957-0.340174949595674
91114.5165646604365-3.51656466043655
101713.24315703350423.75684296649580
111613.93390246533722.06609753466275
122014.39284718607015.60715281392989
132422.2520684393521.74793156064801
142324.2755106280701-1.27551062807010
152023.6100745373425-3.61007453734249
162121.8967761033132-0.896776103313184
171920.6339690803581-1.63396908035812
182320.94235778236212.05764221763789
192322.84905827462250.150941725377507
202324.900592378422-1.90059237842198
212324.1391338895347-1.13913388953469
222725.15599429877571.84400570122431
232623.73069700008992.26930299991007
241724.4983139478705-7.49831394787049
252422.33972450442671.66027549557329
262625.33103675175340.668963248246625
272423.67049623264110.329503767358865
282723.21523830943883.78476169056121
292724.09553185214942.90446814785059
302625.33909461999150.660905380008493
312423.74589841371650.254101586283472
322324.8302576135788-1.83025761357884
332322.30522570490620.694774295093838
342421.67768098606482.32231901393525
351719.0706891947650-2.07068919476503
362115.69220651663895.30779348336107
371921.8533119998816-2.85331199988161
382218.91644942668693.08355057331306
392219.86513555973652.13486444026355
401819.0621097850671-1.06210978506707
411615.81610326604650.183896733953522
421414.8897649480211-0.88976494802113
431212.1820832992101-0.182083299210095
441412.32443096185921.67556903814084
451611.37476567182464.62523432817538
46812.9275719124426-4.92757191244255
4735.26471133980779-2.26471133980779
4803.41663234942047-3.41663234942047
4953.716268558288191.28373144171181
5015.71430583659659-4.71430583659659
5112.10565978654377-1.10565978654377
5233.12229961956307-0.122299619563073
5362.702200415350343.29779958464966
5476.436439294436640.563560705563365
5587.89089672009910.109103279900901
561411.60454409654432.39545590345566
571414.6643100732980-0.664310073297984
581315.9955957692128-2.9955957692128


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
200.3126219572741850.625243914548370.687378042725815
210.2056305555035260.4112611110070520.794369444496474
220.1046795476525150.2093590953050300.895320452347485
230.2757123513568020.5514247027136030.724287648643198
240.7654835702083440.4690328595833120.234516429791656
250.7860685892188850.427862821562230.213931410781115
260.6968431948166210.6063136103667580.303156805183379
270.6232605997819460.7534788004361080.376739400218054
280.5905772849157830.8188454301684340.409422715084217
290.5425391371148120.9149217257703750.457460862885188
300.4415128956645960.8830257913291920.558487104335404
310.332313247257190.664626494514380.66768675274281
320.3921644045617320.7843288091234630.607835595438268
330.6045166896579250.790966620684150.395483310342075
340.500638259068490.9987234818630210.499361740931510
350.5258566177100220.9482867645799560.474143382289978
360.4211543910206550.842308782041310.578845608979345
370.814226020999870.371547958000260.18577397900013
380.735572607579720.5288547848405610.264427392420281


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level00OK