Multiple Linear Regression - Estimated Regression Equation |
PS[t] = + 3.98678631006288 -0.0139630483503009SWS[t] + 0.0119435681086067L[t] + 3.63660450881043e-06Wb[t] -1.02179702553102e-06Wbr[t] -0.00750615624554444Tg[t] + 0.924263159311339P[t] + 0.2630780264437S[t] -1.71362938051807`D `[t] + 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) | 3.98678631006288 | 0.812241 | 4.9084 | 3e-05 | 1.5e-05 |
SWS | -0.0139630483503009 | 0.053604 | -0.2605 | 0.796268 | 0.398134 |
L | 0.0119435681086067 | 0.016036 | 0.7448 | 0.462186 | 0.231093 |
Wb | 3.63660450881043e-06 | 2e-06 | 1.9109 | 0.065621 | 0.03281 |
Wbr | -1.02179702553102e-06 | 1e-06 | -0.899 | 0.375825 | 0.187912 |
Tg | -0.00750615624554444 | 0.00233 | -3.2217 | 0.003062 | 0.001531 |
P | 0.924263159311339 | 0.330794 | 2.7941 | 0.008982 | 0.004491 |
S | 0.2630780264437 | 0.20485 | 1.2842 | 0.208885 | 0.104443 |
`D ` | -1.71362938051807 | 0.419191 | -4.0879 | 3e-04 | 0.00015 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.831725417344077 |
R-squared | 0.691767169856179 |
Adjusted R-squared | 0.609571748484493 |
F-TEST (value) | 8.41612778804339 |
F-TEST (DF numerator) | 8 |
F-TEST (DF denominator) | 30 |
p-value | 6.32987895032855e-06 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 0.878263099112862 |
Sum Squared Residuals | 23.1403821378998 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 2 | 1.52917870659566 | 0.470821293404342 |
2 | 1.8 | 1.89049067430249 | -0.0904906743024908 |
3 | 0.7 | 0.580891617242521 | 0.119108382757479 |
4 | 3.9 | 3.20409405393737 | 0.695905946062635 |
5 | 1 | -0.0980520476239686 | 1.09805204762397 |
6 | 3.6 | 3.41875376932244 | 0.181246230677561 |
7 | 1.4 | 1.95546188289337 | -0.555461882893371 |
8 | 1.5 | 1.88868068032156 | -0.388680680321562 |
9 | 0.7 | 0.818541674584192 | -0.118541674584192 |
10 | 2.1 | 3.09784895307491 | -0.997848953074913 |
11 | 4.1 | 2.59488321290878 | 1.50511678709122 |
12 | 1.2 | 2.01992706226638 | -0.81992706226638 |
13 | 0.5 | 0.420309337300904 | 0.0796906626990957 |
14 | 3.4 | 3.36726157661301 | 0.0327384233869904 |
15 | 1.5 | 2.06083304722624 | -0.56083304722624 |
16 | 3.4 | 3.47830920596308 | -0.0783092059630768 |
17 | 0.8 | 2.01800678406329 | -1.21800678406329 |
18 | 0.8 | 0.578752466572474 | 0.221247533427526 |
19 | 2 | 3.12189715307559 | -1.12189715307559 |
20 | 1.9 | 1.44223401950862 | 0.45776598049138 |
21 | 1.3 | 2.53547068103443 | -1.23547068103443 |
22 | 5.6 | 4.16146007937767 | 1.43853992062233 |
23 | 3.1 | 3.3636768343476 | -0.263676834347599 |
24 | 1.8 | 1.79859642021373 | 0.00140357978626561 |
25 | 0.9 | 0.626075948711075 | 0.273924051288925 |
26 | 1.8 | 2.52687616117539 | -0.726876161175386 |
27 | 1.9 | 1.76444668852458 | 0.13555331147542 |
28 | 0.9 | 1.2296436232266 | -0.329643623226598 |
29 | 2.6 | 1.63032245322796 | 0.969677546772037 |
30 | 2.4 | 3.04780085021171 | -0.647800850211707 |
31 | 1.2 | 2.03717943480815 | -0.837179434808153 |
32 | 0.9 | 1.2367749904922 | -0.336774990492199 |
33 | 0.5 | 0.450835054513314 | 0.0491649454866858 |
34 | 0.6 | 0.439122421392722 | 0.160877578607278 |
35 | 2.3 | 2.11826164467355 | 0.181738355326453 |
36 | 0.5 | 0.396397353279159 | 0.103602646720841 |
37 | 2.6 | 3.35379374662198 | -0.753793746621976 |
38 | 0.6 | 0.149439904022473 | 0.450560095977527 |
39 | 6.6 | 4.1455218799968 | 2.4544781200032 |
Goldfeld-Quandt test for Heteroskedasticity | |||
p-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
12 | 0.855719363110878 | 0.288561273778244 | 0.144280636889122 |
13 | 0.751221256309348 | 0.497557487381304 | 0.248778743690652 |
14 | 0.648431002228097 | 0.703137995543807 | 0.351568997771903 |
15 | 0.506149024845379 | 0.987701950309243 | 0.493850975154621 |
16 | 0.395975448824948 | 0.791950897649896 | 0.604024551175052 |
17 | 0.418170837349731 | 0.836341674699463 | 0.581829162650269 |
18 | 0.306069894445073 | 0.612139788890147 | 0.693930105554927 |
19 | 0.322301919184793 | 0.644603838369586 | 0.677698080815207 |
20 | 0.241237721318446 | 0.482475442636892 | 0.758762278681554 |
21 | 0.407306962979114 | 0.814613925958229 | 0.592693037020886 |
22 | 0.509264255046849 | 0.981471489906303 | 0.490735744953151 |
23 | 0.440136751474535 | 0.88027350294907 | 0.559863248525465 |
24 | 0.316327060144605 | 0.63265412028921 | 0.683672939855395 |
25 | 0.220366768422287 | 0.440733536844574 | 0.779633231577713 |
26 | 0.176980306800602 | 0.353960613601203 | 0.823019693199398 |
27 | 0.166127816344483 | 0.332255632688967 | 0.833872183655517 |
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | |||
Description | # significant tests | % significant tests | OK/NOK |
1% type I error level | 0 | 0 | OK |
5% type I error level | 0 | 0 | OK |
10% type I error level | 0 | 0 | OK |