Multiple Linear Regression - Estimated Regression Equation
S[t] = -0.44848360563522 + 1.01946778957491D[t] -0.0701399164268452SWS[t] + 0.236237232406613PS[t] + 0.0731354251388876L[t] + 0.00206321954317301WB[t] -0.00542342168080034Wbr[t] + 0.00257997006234144Tg[t] -0.272489817386976`P `[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)-0.448483605635221.034829-0.43340.6691510.334576
D1.019467789574910.430242.36950.0274690.013735
SWS-0.07013991642684520.056213-1.24780.2258530.112927
PS0.2362372324066130.1650021.43170.166940.08347
L0.07313542513888760.0294312.4850.0214610.010731
WB0.002063219543173010.0020531.00520.3262530.163126
Wbr-0.005423421680800340.002222-2.44130.0235770.011788
Tg0.002579970062341440.0026670.96750.3443040.172152
`P `-0.2724898173869760.348129-0.78270.4425260.221263


Multiple Linear Regression - Regression Statistics
Multiple R0.900009031117382
R-squared0.810016256092849
Adjusted R-squared0.737641496509172
F-TEST (value)11.1919716314407
F-TEST (DF numerator)8
F-TEST (DF denominator)21
p-value4.88135444098869e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.7416523261178
Sum Squared Residuals11.5510116295548


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
110.7106904471707030.289309552829297
222.08093048810084-0.0809304881008395
321.706128176003590.293871823996411
454.450982378575570.549017621424427
511.12598187454436-0.125981874544365
632.534297372886290.465702627113708
712.03019482194413-1.03019482194413
832.640476994471430.359523005528566
955.08179789513783-0.0817978951378251
1011.39837781055102-0.398377810551017
1111.29088913147572-0.290889131475716
1211.27333476719684-0.273334767196844
1310.7469788870291970.253021112970803
1410.4889641498545570.511035850145443
1521.560320847107270.439679152892726
1643.363511828557280.636488171442723
1711.57216977795725-0.572169777957252
1844.22364485357897-0.22364485357897
1954.308921762221870.691078237778132
2012.05137307080173-1.05137307080173
2110.9327112344257850.067288765574215
2232.327061550925130.672938449074866
2321.885568892256150.114431107743847
2422.47972488655911-0.47972488655911
2554.221394734879860.778605265120141
2611.28894251066482-0.288942510664816
2712.56881139006279-1.56881139006279
2820.7348985500941461.26510144990585
2933.99194378204456-0.99194378204456
3010.9289751329211950.0710248670788049


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.07805881522831140.1561176304566230.921941184771689
130.1187271456620970.2374542913241940.881272854337903
140.04839353251232550.0967870650246510.951606467487675
150.04525206040657560.09050412081315130.954747939593424
160.02511359830291020.05022719660582040.97488640169709
170.01419742319081830.02839484638163660.985802576809182
180.00619567976153970.01239135952307940.99380432023846


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.285714285714286NOK
10% type I error level50.714285714285714NOK