Multiple Linear Regression - Estimated Regression Equation

Jaar[t] = + 14 -1.02805203193725e-17VerstrB[t] + 1.50846009476909e-17ExactB[t] + 6.50465008028154e-18VerstrV[t] + 5.03329606373763e-18ExactV[t] -1.04787884319397e-17VerstrW[t] -6.73638633406018e-18`ExactW `[t] + 1t + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	14	0	9879970441506714	0	0
VerstrB	-1.02805203193725e-17	0	-0.8206	0.419087	0.209543
ExactB	1.50846009476909e-17	0	1.2427	0.224647	0.112323
VerstrV	6.50465008028154e-18	0	0.2513	0.803505	0.401753
ExactV	5.03329606373763e-18	0	0.2799	0.781683	0.390842
VerstrW	-1.04787884319397e-17	0	-0.4606	0.648757	0.324379
`ExactW `	-6.73638633406018e-18	0	-0.2041	0.839834	0.419917
t	1	0	19031112378560384	0	0

Multiple Linear Regression - Regression Statistics
Multiple R	1
R-squared	1
Adjusted R-squared	1
F-TEST (value)	1.07985078615822e+32
F-TEST (DF numerator)	7
F-TEST (DF denominator)	27
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.17321760050666e-15
Sum Squared Residuals	1.27517617957102e-28

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	15	15	5.51663672104164e-15
2	16	16	1.00904484738459e-15
3	17	17	-7.2890954398171e-15
4	18	18	-1.43742258638476e-15
5	19	19	2.10004053779115e-15
6	20	20	-4.84049662321525e-16
7	21	21	-1.75198478713631e-15
8	22	22	1.54729164081008e-15
9	23	23	1.6213607302485e-16
10	24	24	2.09804135218996e-15
11	25	25	-3.74063429187803e-16
12	26	26	-9.07319514494898e-16
13	27	27	-2.03759234512508e-16
14	28	28	4.29417446386812e-16
15	29	29	-7.1753937696882e-16
16	30	30	6.14355808761856e-17
17	31	31	-3.05828822486142e-16
18	32	32	-5.97307321439702e-16
19	33	33	1.23560262553748e-15
20	34	34	9.68095383890868e-16
21	35	35	-1.5779803003748e-16
22	36	36	9.78351590927233e-16
23	37	37	3.12423025524816e-17
24	38	38	-1.07335138714874e-15
25	39	39	-1.27734042005247e-15
26	40	40	-1.07114658560709e-15
27	41	41	-4.73461490399311e-16
28	42	42	-1.18981076787204e-15
29	43	43	-9.32565343059672e-16
30	44	44	1.70487203983169e-15
31	45	45	1.59004457865642e-15
32	46	46	1.88567226648649e-15
33	47	47	5.65903941818436e-16
34	48	48	-2.16755319761824e-15
35	49	49	5.27568467338226e-16

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
11	0.264167949923305	0.528335899846611	0.735832050076694
12	4.6015677353884e-05	9.20313547077681e-05	0.999953984322646
13	0.365500291579228	0.731000583158456	0.634499708420772
14	0.847789090437231	0.304421819125538	0.152210909562769
15	0.742055920438123	0.515888159123754	0.257944079561877
16	8.76092349709768e-09	1.75218469941954e-08	0.999999991239076
17	0.000235991497581452	0.000471982995162904	0.999764008502419
18	0.0155318971774855	0.0310637943549711	0.984468102822514
19	0.999999981898631	3.62027384421256e-08	1.81013692210628e-08
20	0.384535546240221	0.769071092480443	0.615464453759779
21	0.987744972125951	0.0245100557480982	0.0122550278740491
22	0.97852602951021	0.0429479409795795	0.0214739704897897
23	0.999429656358657	0.00114068728268675	0.000570343641343376
24	0.751490259540581	0.497019480918838	0.248509740459419

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	5	0.357142857142857	NOK
5% type I error level	8	0.571428571428571	NOK
10% type I error level	8	0.571428571428571	NOK