| Multiple Linear Regression - Estimated Regression Equation |
| Y[t] = + 4.92846343476301e-11 -2.98615544369428e-12X[t] + 1Y1[t] + 8.76083176041636e-18Y2[t] -3.59960750140816e-13M1[t] + 1.91039989183012e-13M2[t] + 9.58085589102287e-12M3[t] + 1.62581264265537e-12M4[t] + 2.27350604296845e-12M5[t] -4.41959246781001e-14M6[t] -1.80473205404753e-12M7[t] -1.53258490248065e-12M8[t] -7.35980514667547e-13M9[t] + 1.80890479746526e-13M10[t] + 1.87338371298928e-13M11[t] -5.19452604930502e-14t + 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) | 4.92846343476301e-11 | 0 | 4.1656 | 7.9e-05 | 3.9e-05 |
| X | -2.98615544369428e-12 | 0 | -0.9624 | 0.338791 | 0.169395 |
| Y1 | 1 | 0 | 3359192303481257 | 0 | 0 |
| Y2 | 8.76083176041636e-18 | 0 | 0.0288 | 0.977115 | 0.488557 |
| M1 | -3.59960750140816e-13 | 0 | -0.1008 | 0.919954 | 0.459977 |
| M2 | 1.91039989183012e-13 | 0 | 0.0516 | 0.958966 | 0.479483 |
| M3 | 9.58085589102287e-12 | 0 | 2.5791 | 0.011761 | 0.005881 |
| M4 | 1.62581264265537e-12 | 0 | 0.4112 | 0.682011 | 0.341005 |
| M5 | 2.27350604296845e-12 | 0 | 0.5708 | 0.56973 | 0.284865 |
| M6 | -4.41959246781001e-14 | 0 | -0.0039 | 0.996871 | 0.498436 |
| M7 | -1.80473205404753e-12 | 0 | -0.2813 | 0.779195 | 0.389597 |
| M8 | -1.53258490248065e-12 | 0 | -0.3712 | 0.71148 | 0.35574 |
| M9 | -7.35980514667547e-13 | 0 | -0.1582 | 0.874688 | 0.437344 |
| M10 | 1.80890479746526e-13 | 0 | 0.0415 | 0.967013 | 0.483507 |
| M11 | 1.87338371298928e-13 | 0 | 0.0529 | 0.957978 | 0.478989 |
| t | -5.19452604930502e-14 | 0 | -0.9922 | 0.324132 | 0.162066 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 1 |
| R-squared | 1 |
| Adjusted R-squared | 1 |
| F-TEST (value) | 5.04145999650029e+31 |
| F-TEST (DF numerator) | 15 |
| F-TEST (DF denominator) | 79 |
| p-value | 0 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 6.77646115224013e-12 |
| Sum Squared Residuals | 3.62771363407775e-21 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 142773 | 142773 | -6.97076020479089e-12 |
| 2 | 133639 | 133639 | -4.62525687717883e-12 |
| 3 | 128332 | 128332 | 5.44183115870851e-11 |
| 4 | 120297 | 120297 | -3.40053118173447e-12 |
| 5 | 118632 | 118632 | -3.18394361020532e-12 |
| 6 | 155276 | 155276 | -2.57676634316205e-12 |
| 7 | 169316 | 169316 | -6.5738652310142e-14 |
| 8 | 167395 | 167395 | -3.19090256683984e-12 |
| 9 | 157939 | 157939 | -3.34301268480542e-12 |
| 10 | 149601 | 149601 | -2.22858031249122e-12 |
| 11 | 146310 | 146310 | -2.4625185072201e-12 |
| 12 | 141579 | 141579 | -1.90520641912936e-12 |
| 13 | 136473 | 136473 | -5.40804853090086e-13 |
| 14 | 129818 | 129818 | -3.03322622107426e-13 |
| 15 | 124226 | 124226 | -1.07290116431453e-11 |
| 16 | 116428 | 116428 | -1.01714685867044e-12 |
| 17 | 116440 | 116440 | -1.54992536523827e-12 |
| 18 | 147747 | 147747 | -3.98203146897926e-13 |
| 19 | 160069 | 160069 | -2.53182729282213e-12 |
| 20 | 163129 | 163129 | -5.85571213715199e-13 |
| 21 | 151108 | 151108 | -1.45731604890662e-12 |
| 22 | 141481 | 141481 | -1.56500888007174e-12 |
| 23 | 139174 | 139174 | -4.07146249988704e-13 |
| 24 | 134066 | 134066 | 8.21668768276585e-14 |
| 25 | 130104 | 130104 | 7.12718539250577e-13 |
| 26 | 123090 | 123090 | -2.64089300562253e-13 |
| 27 | 116598 | 116598 | -8.46659381828784e-12 |
| 28 | 109627 | 109627 | -9.34354041977796e-13 |
| 29 | 105428 | 105428 | 4.02090450770148e-13 |
| 30 | 137272 | 137272 | 4.41916686385895e-13 |
| 31 | 159836 | 159836 | -1.71288707538038e-12 |
| 32 | 155283 | 155283 | -1.01901181872110e-13 |
| 33 | 141514 | 141514 | 7.81473043696383e-13 |
| 34 | 131852 | 131852 | 7.04690533827093e-13 |
| 35 | 130691 | 130691 | 4.42694807366088e-13 |
| 36 | 128461 | 128461 | 7.76367744610878e-13 |
| 37 | 123066 | 123066 | 8.83398016398544e-13 |
| 38 | 117599 | 117599 | 1.04877352990937e-12 |
| 39 | 111599 | 111599 | -5.56753523644028e-12 |
| 40 | 105395 | 105395 | 1.61861052151793e-12 |
| 41 | 102334 | 102334 | 2.4412300609666e-12 |
| 42 | 131305 | 131305 | 1.47759031385716e-12 |
| 43 | 149033 | 149033 | 1.38689493736117e-13 |
| 44 | 144954 | 144954 | 1.58082312342448e-12 |
| 45 | 132404 | 132404 | 1.91684482289470e-12 |
| 46 | 122104 | 122104 | 1.20418801869533e-12 |
| 47 | 118755 | 118755 | 1.01328401782209e-12 |
| 48 | 116222 | 116222 | -3.66583030304323e-13 |
| 49 | 110924 | 110924 | 6.09372201687507e-13 |
| 50 | 103753 | 103753 | -2.85770229223607e-13 |
| 51 | 99983 | 99983 | -7.88086321980542e-12 |
| 52 | 93302 | 93302 | -5.01697637255762e-13 |
| 53 | 91496 | 91496 | -2.34141071347797e-13 |
| 54 | 119321 | 119321 | 2.11389323339096e-13 |
| 55 | 139261 | 139261 | 6.25320839405668e-13 |
| 56 | 133739 | 133739 | -9.46886526784736e-13 |
| 57 | 123913 | 123913 | 4.616692582237e-13 |
| 58 | 113438 | 113438 | 2.57877236088505e-13 |
| 59 | 109416 | 109416 | 1.27789733128369e-12 |
| 60 | 109406 | 109406 | -2.62116264450192e-13 |
| 61 | 105645 | 105645 | 1.82582058110069e-12 |
| 62 | 101328 | 101328 | 1.46442816736043e-12 |
| 63 | 97686 | 97686 | -6.21270645376455e-12 |
| 64 | 93093 | 93093 | 2.34901832418257e-13 |
| 65 | 91382 | 91382 | 4.41832730154226e-13 |
| 66 | 122257 | 122257 | 4.3691179031731e-13 |
| 67 | 139183 | 139183 | 1.25769982657461e-12 |
| 68 | 139887 | 139887 | 5.75501905279789e-13 |
| 69 | 131822 | 131822 | -2.19450391589948e-13 |
| 70 | 116805 | 116805 | 2.21053179561928e-13 |
| 71 | 113706 | 113706 | 8.69565956885385e-13 |
| 72 | 113012 | 113012 | 1.44525348746748e-12 |
| 73 | 110452 | 110452 | 2.094509147549e-12 |
| 74 | 107005 | 107005 | 1.33491334573885e-12 |
| 75 | 102841 | 102841 | -7.93622362508816e-12 |
| 76 | 98173 | 98173 | 2.18735745246233e-12 |
| 77 | 98181 | 98181 | 1.62893998675624e-12 |
| 78 | 137277 | 137277 | 1.12882204362521e-12 |
| 79 | 147579 | 147579 | 1.64608353994517e-12 |
| 80 | 146571 | 146571 | 1.78480351657972e-12 |
| 81 | 138920 | 138920 | 8.20366781548175e-13 |
| 82 | 130340 | 130340 | 2.07834327435405e-13 |
| 83 | 128140 | 128140 | -5.10145421152348e-13 |
| 84 | 127059 | 127059 | 2.30117604977839e-13 |
| 85 | 122860 | 122860 | 1.38574657189466e-12 |
| 86 | 117702 | 117702 | 1.63032398606346e-12 |
| 87 | 113537 | 113537 | -7.62537759055352e-12 |
| 88 | 108366 | 108366 | 1.81285991323993e-12 |
| 89 | 111078 | 111078 | 5.39168181441674e-14 |
| 90 | 150739 | 150739 | -7.21660667464705e-13 |
| 91 | 159129 | 159129 | 6.42659320851088e-13 |
| 92 | 157928 | 157928 | 8.84132943927921e-13 |
| 93 | 147768 | 147768 | 1.03942521893901e-12 |
| 94 | 137507 | 137507 | 1.19794589695471e-12 |
| 95 | 136919 | 136919 | -2.23631934996096e-13 |
| Goldfeld-Quandt test for Heteroskedasticity | |||
| p-values | Alternative Hypothesis | ||
| breakpoint index | greater | 2-sided | less |
| 19 | 0 | 0 | 1 |
| 20 | 0.99998051905601 | 3.89618879815751e-05 | 1.94809439907876e-05 |
| 21 | 5.74677351011148e-11 | 1.14935470202230e-10 | 0.999999999942532 |
| 22 | 0.000241425322712505 | 0.000482850645425009 | 0.999758574677287 |
| 23 | 0.634960321146947 | 0.730079357706106 | 0.365039678853053 |
| 24 | 0.999999707964615 | 5.84070769135105e-07 | 2.92035384567552e-07 |
| 25 | 0.184083985183864 | 0.368167970367727 | 0.815916014816136 |
| 26 | 1 | 1.88675465857786e-18 | 9.43377329288929e-19 |
| 27 | 0.398091625361893 | 0.796183250723786 | 0.601908374638107 |
| 28 | 0.0203382305020757 | 0.0406764610041513 | 0.979661769497924 |
| 29 | 0.0593147742654999 | 0.118629548531000 | 0.9406852257345 |
| 30 | 0.00383863458627132 | 0.00767726917254264 | 0.996161365413729 |
| 31 | 0.166483997141679 | 0.332967994283357 | 0.833516002858321 |
| 32 | 1 | 1.42464844856028e-33 | 7.12324224280138e-34 |
| 33 | 0.000908685164452963 | 0.00181737032890593 | 0.999091314835547 |
| 34 | 0.998028682081328 | 0.00394263583734496 | 0.00197131791867248 |
| 35 | 0.141821516108999 | 0.283643032217997 | 0.858178483891001 |
| 36 | 0.999845051778694 | 0.000309896442612286 | 0.000154948221306143 |
| 37 | 9.170981533742e-13 | 1.8341963067484e-12 | 0.999999999999083 |
| 38 | 0.937976028630722 | 0.124047942738556 | 0.0620239713692782 |
| 39 | 2.09562493592928e-11 | 4.19124987185856e-11 | 0.999999999979044 |
| 40 | 0.00802944149110447 | 0.0160588829822089 | 0.991970558508896 |
| 41 | 0.00217995488652272 | 0.00435990977304545 | 0.997820045113477 |
| 42 | 0.999999995481257 | 9.03748692899215e-09 | 4.51874346449607e-09 |
| 43 | 0.824453291965989 | 0.351093416068022 | 0.175546708034011 |
| 44 | 0.962150405743702 | 0.0756991885125954 | 0.0378495942562977 |
| 45 | 2.28085882460876e-15 | 4.56171764921753e-15 | 0.999999999999998 |
| 46 | 0.999285828936187 | 0.00142834212762701 | 0.000714171063813504 |
| 47 | 0.103787733551610 | 0.207575467103221 | 0.89621226644839 |
| 48 | 0.99999975854879 | 4.82902421120387e-07 | 2.41451210560194e-07 |
| 49 | 1.57360404677747e-08 | 3.14720809355495e-08 | 0.99999998426396 |
| 50 | 2.93809074304749e-07 | 5.87618148609497e-07 | 0.999999706190926 |
| 51 | 0.997031199033838 | 0.00593760193232342 | 0.00296880096616171 |
| 52 | 0.999999692553607 | 6.14892785833258e-07 | 3.07446392916629e-07 |
| 53 | 0.999999999718613 | 5.62774842786012e-10 | 2.81387421393006e-10 |
| 54 | 0.313195948051021 | 0.626391896102042 | 0.686804051948979 |
| 55 | 0.199142779352543 | 0.398285558705086 | 0.800857220647457 |
| 56 | 0.999999999973853 | 5.2294254431622e-11 | 2.6147127215811e-11 |
| 57 | 0.98413535257619 | 0.0317292948476209 | 0.0158646474238105 |
| 58 | 0.99999999999999 | 2.14518213266390e-14 | 1.07259106633195e-14 |
| 59 | 0.000756823711712867 | 0.00151364742342573 | 0.999243176288287 |
| 60 | 1 | 4.50893324638215e-22 | 2.25446662319107e-22 |
| 61 | 0.852177202015498 | 0.295645595969003 | 0.147822797984502 |
| 62 | 0.999999999999986 | 2.69318134736742e-14 | 1.34659067368371e-14 |
| 63 | 0.239401048834182 | 0.478802097668365 | 0.760598951165818 |
| 64 | 0.999997848932304 | 4.30213539193941e-06 | 2.15106769596971e-06 |
| 65 | 0.965937989032791 | 0.068124021934417 | 0.0340620109672085 |
| 66 | 0.792126943980917 | 0.415746112038166 | 0.207873056019083 |
| 67 | 4.55520669046499e-08 | 9.11041338092998e-08 | 0.999999954447933 |
| 68 | 0.318325234438146 | 0.636650468876293 | 0.681674765561854 |
| 69 | 0.297920548272017 | 0.595841096544033 | 0.702079451727983 |
| 70 | 0.888523355220326 | 0.222953289559347 | 0.111476644779674 |
| 71 | 9.99011669378782e-06 | 1.99802333875756e-05 | 0.999990009883306 |
| 72 | 0.98938086351133 | 0.0212382729773395 | 0.0106191364886698 |
| 73 | 6.93940152158611e-11 | 1.38788030431722e-10 | 0.999999999930606 |
| 74 | 0.963666804141513 | 0.0726663917169746 | 0.0363331958584873 |
| 75 | 1.64297341712738e-07 | 3.28594683425475e-07 | 0.999999835702658 |
| 76 | 0.947680781315557 | 0.104638437368885 | 0.0523192186844426 |
| Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | |||
| Description | # significant tests | % significant tests | OK/NOK |
| 1% type I error level | 33 | 0.568965517241379 | NOK |
| 5% type I error level | 37 | 0.637931034482759 | NOK |
| 10% type I error level | 40 | 0.689655172413793 | NOK |
