| Multiple Linear Regression - Estimated Regression Equation |
| Y[t] = -1.26945508398474e-14 -2.22449408643527e-17X[t] -5.7380076558157e-17Y1[t] + 1.99131271067708e-16Y2[t] -5.19124269428038e-16Y3[t] + 1Y4[t] -1.36208603520825e-15M1[t] + 7.14770130673045e-16M2[t] -2.34701997419123e-15M3[t] -2.93422111390953e-15M4[t] -2.67617627599303e-15M5[t] + 1.68530062700541e-15M6[t] -7.7618351318877e-16M7[t] -8.7509539066569e-16M8[t] -1.06494618745309e-15M9[t] -1.50208739479063e-15M10[t] -4.61356709651356e-16M11[t] -1.42183864708931e-17t + 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) | -1.26945508398474e-14 | 0 | -0.9192 | 0.363636 | 0.181818 |
| X | -2.22449408643527e-17 | 0 | -0.1548 | 0.877805 | 0.438903 |
| Y1 | -5.7380076558157e-17 | 0 | -0.6817 | 0.499444 | 0.249722 |
| Y2 | 1.99131271067708e-16 | 0 | 1.5547 | 0.128093 | 0.064046 |
| Y3 | -5.19124269428038e-16 | 0 | -4.1327 | 0.000184 | 9.2e-05 |
| Y4 | 1 | 0 | 12326495874143028 | 0 | 0 |
| M1 | -1.36208603520825e-15 | 0 | -0.4174 | 0.678665 | 0.339332 |
| M2 | 7.14770130673045e-16 | 0 | 0.1957 | 0.845873 | 0.422937 |
| M3 | -2.34701997419123e-15 | 0 | -0.4813 | 0.632975 | 0.316488 |
| M4 | -2.93422111390953e-15 | 0 | -0.5008 | 0.619318 | 0.309659 |
| M5 | -2.67617627599303e-15 | 0 | -0.4912 | 0.626007 | 0.313004 |
| M6 | 1.68530062700541e-15 | 0 | 0.3977 | 0.693012 | 0.346506 |
| M7 | -7.7618351318877e-16 | 0 | -0.2173 | 0.829139 | 0.41457 |
| M8 | -8.7509539066569e-16 | 0 | -0.2581 | 0.797678 | 0.398839 |
| M9 | -1.06494618745309e-15 | 0 | -0.339 | 0.736429 | 0.368214 |
| M10 | -1.50208739479063e-15 | 0 | -0.4862 | 0.629576 | 0.314788 |
| M11 | -4.61356709651356e-16 | 0 | -0.1685 | 0.867037 | 0.433519 |
| t | -1.42183864708931e-17 | 0 | -0.1809 | 0.857411 | 0.428705 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 1 |
| R-squared | 1 |
| Adjusted R-squared | 1 |
| F-TEST (value) | 2.80584054414827e+32 |
| F-TEST (DF numerator) | 17 |
| F-TEST (DF denominator) | 39 |
| p-value | 0 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 2.91412542240633e-15 |
| Sum Squared Residuals | 3.3119295212308e-28 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 423 | 423 | -1.5756660649759e-15 |
| 2 | 427 | 427 | 2.05826417672047e-15 |
| 3 | 441 | 441 | -1.37862820027747e-15 |
| 4 | 449 | 449 | -1.21580093961209e-15 |
| 5 | 452 | 452 | -2.02414321847352e-15 |
| 6 | 462 | 462 | 1.47573744853726e-14 |
| 7 | 455 | 455 | -6.54641376215501e-16 |
| 8 | 461 | 461 | -1.1016798355215e-15 |
| 9 | 461 | 461 | -7.06789786257863e-16 |
| 10 | 463 | 463 | 1.20517493284047e-16 |
| 11 | 462 | 462 | -1.82892527268994e-15 |
| 12 | 456 | 456 | -3.60995230708738e-16 |
| 13 | 455 | 455 | -1.84022052772984e-16 |
| 14 | 456 | 456 | -4.79024480723306e-16 |
| 15 | 472 | 472 | -2.41970383018809e-16 |
| 16 | 472 | 472 | 2.50641779754823e-16 |
| 17 | 471 | 471 | -2.64946915677257e-16 |
| 18 | 465 | 465 | -4.05587282464333e-15 |
| 19 | 459 | 459 | -5.83982853098776e-16 |
| 20 | 465 | 465 | -5.97858284924235e-16 |
| 21 | 468 | 468 | -3.17149285580468e-16 |
| 22 | 467 | 467 | 5.58347472896395e-16 |
| 23 | 463 | 463 | 8.4947621776597e-16 |
| 24 | 460 | 460 | 2.63288391538352e-16 |
| 25 | 462 | 462 | 2.68497714247626e-15 |
| 26 | 461 | 461 | -3.30552625562589e-16 |
| 27 | 476 | 476 | -4.04822303853878e-16 |
| 28 | 476 | 476 | 4.59532949691034e-16 |
| 29 | 471 | 471 | -4.75808655795954e-16 |
| 30 | 453 | 453 | -4.31759982777839e-15 |
| 31 | 443 | 443 | -4.62580974135499e-16 |
| 32 | 442 | 442 | -2.14530336827656e-16 |
| 33 | 444 | 444 | -1.13820253539286e-16 |
| 34 | 438 | 438 | 1.96873641622148e-16 |
| 35 | 427 | 427 | -3.3488550983607e-16 |
| 36 | 424 | 424 | 3.11964772464467e-16 |
| 37 | 416 | 416 | -1.90394293208803e-15 |
| 38 | 406 | 406 | 5.09484047473316e-16 |
| 39 | 431 | 431 | 4.111946569591e-16 |
| 40 | 434 | 434 | -6.64743970712905e-16 |
| 41 | 418 | 418 | 1.06155131207386e-15 |
| 42 | 412 | 412 | -4.05772806784273e-15 |
| 43 | 404 | 404 | 1.41899780458316e-16 |
| 44 | 409 | 409 | 5.25470132693299e-17 |
| 45 | 412 | 412 | 2.81578831769808e-16 |
| 46 | 406 | 406 | -8.75738607802591e-16 |
| 47 | 398 | 398 | 1.31433456476004e-15 |
| 48 | 397 | 397 | -2.14257933294079e-16 |
| 49 | 385 | 385 | 9.7865390736065e-16 |
| 50 | 390 | 390 | -1.75817111790789e-15 |
| 51 | 413 | 413 | 1.61422623019105e-15 |
| 52 | 413 | 413 | 1.17037018087915e-15 |
| 53 | 401 | 401 | 1.70334747787287e-15 |
| 54 | 397 | 397 | -2.32617376510813e-15 |
| 55 | 397 | 397 | 1.55930542299146e-15 |
| 56 | 409 | 409 | 1.86152144400406e-15 |
| 57 | 419 | 419 | 8.5618049360781e-16 |
| Goldfeld-Quandt test for Heteroskedasticity | |||
| p-values | Alternative Hypothesis | ||
| breakpoint index | greater | 2-sided | less |
| 21 | 0.0220413330450448 | 0.0440826660900896 | 0.977958666954955 |
| 22 | 0.0554475503200496 | 0.110895100640099 | 0.94455244967995 |
| 23 | 0.697260287219368 | 0.605479425561264 | 0.302739712780632 |
| 24 | 0.456140005113539 | 0.912280010227078 | 0.543859994886461 |
| 25 | 0.000210817126106338 | 0.000421634252212677 | 0.999789182873894 |
| 26 | 0.0948237779338887 | 0.189647555867777 | 0.905176222066111 |
| 27 | 1.51425479954453e-05 | 3.02850959908905e-05 | 0.999984857452004 |
| 28 | 0.978362587340182 | 0.0432748253196357 | 0.0216374126598178 |
| 29 | 0.158051724666437 | 0.316103449332875 | 0.841948275333563 |
| 30 | 0.91105876803398 | 0.177882463932039 | 0.0889412319660196 |
| 31 | 0.99978982336655 | 0.000420353266898711 | 0.000210176633449356 |
| 32 | 2.12272602757383e-09 | 4.24545205514767e-09 | 0.999999997877274 |
| 33 | 0.983563755433518 | 0.0328724891329645 | 0.0164362445664823 |
| 34 | 0.331948487731929 | 0.663896975463858 | 0.668051512268071 |
| 35 | 0.937398562519642 | 0.125202874960716 | 0.0626014374803581 |
| 36 | 1 | 0 | 0 |
| Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | |||
| Description | # significant tests | % significant tests | OK/NOK |
| 1% type I error level | 5 | 0.3125 | NOK |
| 5% type I error level | 8 | 0.5 | NOK |
| 10% type I error level | 8 | 0.5 | NOK |
