| Multiple Linear Regression - Estimated Regression Equation |
| Uitvoer[t] = -331.141725919585 + 1.70620646635698TIP[t] + 2.72941331902169`index/cons`[t] + 3.85690559007307M1[t] + 5.18062213837092M2[t] + 7.79403001839284M3[t] + 5.82862661097082M4[t] + 3.69147814714131M5[t] + 4.56365482328584M6[t] + 6.54365000251388M7[t] + 1.06346039581491M8[t] + 32.5649038799904M9[t] + 3.02441373941594M10[t] -1.30786415664453M11[t] -0.303331431381687t + 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) | -331.141725919585 | 63.565908 | -5.2094 | 3e-06 | 1e-06 |
| TIP | 1.70620646635698 | 0.106402 | 16.0355 | 0 | 0 |
| `index/cons` | 2.72941331902169 | 0.650476 | 4.196 | 1e-04 | 5e-05 |
| M1 | 3.85690559007307 | 3.131585 | 1.2316 | 0.223333 | 0.111667 |
| M2 | 5.18062213837092 | 3.391212 | 1.5277 | 0.132328 | 0.066164 |
| M3 | 7.79403001839284 | 3.395492 | 2.2954 | 0.025548 | 0.012774 |
| M4 | 5.82862661097082 | 3.344886 | 1.7425 | 0.087002 | 0.043501 |
| M5 | 3.69147814714131 | 3.039682 | 1.2144 | 0.229772 | 0.114886 |
| M6 | 4.56365482328584 | 3.208112 | 1.4225 | 0.160518 | 0.080259 |
| M7 | 6.54365000251388 | 3.26036 | 2.007 | 0.049671 | 0.024836 |
| M8 | 1.06346039581491 | 3.018328 | 0.3523 | 0.725934 | 0.362967 |
| M9 | 32.5649038799904 | 4.146076 | 7.8544 | 0 | 0 |
| M10 | 3.02441373941594 | 3.492558 | 0.866 | 0.390274 | 0.195137 |
| M11 | -1.30786415664453 | 3.147305 | -0.4156 | 0.679356 | 0.339678 |
| t | -0.303331431381687 | 0.153034 | -1.9821 | 0.052471 | 0.026236 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.957608253516359 |
| R-squared | 0.917013567202651 |
| Adjusted R-squared | 0.895889747945144 |
| F-TEST (value) | 43.4113526547414 |
| F-TEST (DF numerator) | 14 |
| F-TEST (DF denominator) | 55 |
| p-value | 0 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 4.97581886189116 |
| Sum Squared Residuals | 1361.73253404935 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 103.34 | 103.568190843265 | -0.228190843264547 |
| 2 | 102.6 | 101.688024967374 | 0.9119750326261 |
| 3 | 100.69 | 97.4332807282237 | 3.25671927177625 |
| 4 | 105.67 | 103.291988016547 | 2.37801198345283 |
| 5 | 123.61 | 127.857302708662 | -4.24730270866232 |
| 6 | 113.08 | 113.124619509018 | -0.0446195090180228 |
| 7 | 106.46 | 106.345148220368 | 0.114851779631629 |
| 8 | 123.38 | 124.202870512573 | -0.822870512573485 |
| 9 | 109.87 | 111.668025787398 | -1.79802578739765 |
| 10 | 95.74 | 102.284194576012 | -6.54419457601223 |
| 11 | 123.06 | 126.920309917834 | -3.86030991783389 |
| 12 | 123.39 | 122.833258863641 | 0.55674113635875 |
| 13 | 120.28 | 115.003111373414 | 5.27688862658569 |
| 14 | 115.33 | 111.171221089242 | 4.15877891075798 |
| 15 | 110.4 | 108.63432690284 | 1.76567309716024 |
| 16 | 114.49 | 110.030249529382 | 4.45975047061834 |
| 17 | 132.03 | 124.105563863574 | 7.92443613642618 |
| 18 | 123.16 | 121.350734422688 | 1.80926557731227 |
| 19 | 118.82 | 115.52681630927 | 3.29318369072957 |
| 20 | 128.32 | 137.192651837054 | -8.87265183705398 |
| 21 | 112.24 | 113.205009960866 | -0.965009960866323 |
| 22 | 104.53 | 108.667632357374 | -4.1376323573739 |
| 23 | 132.57 | 133.590400726087 | -1.02040072608655 |
| 24 | 122.52 | 121.67562598271 | 0.844374017290262 |
| 25 | 131.8 | 131.023317022733 | 0.77668297726693 |
| 26 | 124.55 | 121.171713173851 | 3.3782868261494 |
| 27 | 120.96 | 118.015073082654 | 2.94492691734593 |
| 28 | 122.6 | 119.984301762978 | 2.61569823702211 |
| 29 | 145.52 | 142.577324504328 | 2.94267549567173 |
| 30 | 118.57 | 118.904196975046 | -0.334196975045805 |
| 31 | 134.25 | 137.233254875034 | -2.98325487503401 |
| 32 | 136.7 | 139.414315962451 | -2.71431596245073 |
| 33 | 121.37 | 121.664611459708 | -0.294611459707655 |
| 34 | 111.63 | 117.939331261215 | -6.30933126121468 |
| 35 | 134.42 | 137.647886136297 | -3.22788613629694 |
| 36 | 137.65 | 141.443793321606 | -3.79379332160576 |
| 37 | 137.86 | 139.564671664358 | -1.70467166435766 |
| 38 | 119.77 | 122.260347629885 | -2.49034762988493 |
| 39 | 130.69 | 132.050309140518 | -1.36030914051828 |
| 40 | 128.28 | 130.061112967536 | -1.78111296753637 |
| 41 | 147.45 | 150.026655304769 | -2.57665530476948 |
| 42 | 128.42 | 129.881973088456 | -1.46197308845622 |
| 43 | 136.9 | 136.36343833208 | 0.536561667920284 |
| 44 | 143.95 | 143.895183579078 | 0.0548164209220742 |
| 45 | 135.64 | 134.096349506843 | 1.54365049315655 |
| 46 | 122.48 | 124.133261191693 | -1.65326119169327 |
| 47 | 136.83 | 133.768342067775 | 3.06165793222511 |
| 48 | 153.04 | 152.974437203102 | 0.0655627968976921 |
| 49 | 142.71 | 143.021298374021 | -0.311298374021209 |
| 50 | 123.46 | 122.741138281091 | 0.718861718909419 |
| 51 | 144.37 | 144.426683380549 | -0.0566833805493945 |
| 52 | 146.15 | 148.088277575454 | -1.938277575454 |
| 53 | 147.61 | 142.194120405775 | 5.41587959422492 |
| 54 | 158.51 | 156.023514412449 | 2.486485587551 |
| 55 | 147.4 | 145.647168592674 | 1.75283140732649 |
| 56 | 165.05 | 152.612205119809 | 12.4377948801906 |
| 57 | 154.64 | 151.494456483512 | 3.14554351648761 |
| 58 | 126.2 | 127.206218955245 | -1.00621895524531 |
| 59 | 157.36 | 152.313061152008 | 5.04693884799228 |
| 60 | 154.15 | 151.822884628941 | 2.32711537105906 |
| 61 | 123.21 | 127.019410722209 | -3.8094107222092 |
| 62 | 113.07 | 119.747554858558 | -6.67755485855797 |
| 63 | 110.45 | 117.000326765215 | -6.55032676521474 |
| 64 | 113.57 | 119.304070148103 | -5.73407014810291 |
| 65 | 122.44 | 131.899033212891 | -9.45903321289103 |
| 66 | 114.93 | 117.384961592343 | -2.45496159234323 |
| 67 | 111.85 | 114.564173670574 | -2.71417367057397 |
| 68 | 126.04 | 126.122772989034 | -0.0827729890344318 |
| 69 | 121.34 | 122.971546801673 | -1.63154680167253 |
| 70 | 124.36 | 104.709361658461 | 19.6506383415394 |
| Goldfeld-Quandt test for Heteroskedasticity | |||
| p-values | Alternative Hypothesis | ||
| breakpoint index | greater | 2-sided | less |
| 18 | 0.0273629670689887 | 0.0547259341379775 | 0.972637032931011 |
| 19 | 0.0078431565959315 | 0.015686313191863 | 0.992156843404069 |
| 20 | 0.028767022905758 | 0.0575340458115159 | 0.971232977094242 |
| 21 | 0.0198251095484606 | 0.0396502190969213 | 0.980174890451539 |
| 22 | 0.00796201856509791 | 0.0159240371301958 | 0.992037981434902 |
| 23 | 0.00278198616206869 | 0.00556397232413738 | 0.997218013837931 |
| 24 | 0.0205162084541185 | 0.0410324169082371 | 0.979483791545881 |
| 25 | 0.00969268580796558 | 0.0193853716159312 | 0.990307314192034 |
| 26 | 0.00506209444038286 | 0.0101241888807657 | 0.994937905559617 |
| 27 | 0.00309362108050353 | 0.00618724216100706 | 0.996906378919497 |
| 28 | 0.00361448752320183 | 0.00722897504640367 | 0.996385512476798 |
| 29 | 0.00211572156057753 | 0.00423144312115506 | 0.997884278439423 |
| 30 | 0.00785526891751669 | 0.0157105378350334 | 0.992144731082483 |
| 31 | 0.00409704456086849 | 0.00819408912173697 | 0.995902955439132 |
| 32 | 0.00201022645932764 | 0.00402045291865529 | 0.997989773540672 |
| 33 | 0.00116720441268778 | 0.00233440882537556 | 0.998832795587312 |
| 34 | 0.000897991372071044 | 0.00179598274414209 | 0.999102008627929 |
| 35 | 0.000604123084927316 | 0.00120824616985463 | 0.999395876915073 |
| 36 | 0.000348411509173057 | 0.000696823018346115 | 0.999651588490827 |
| 37 | 0.000162090838077284 | 0.000324181676154569 | 0.999837909161923 |
| 38 | 0.000324140481687829 | 0.000648280963375658 | 0.999675859518312 |
| 39 | 0.000150880923397256 | 0.000301761846794512 | 0.999849119076603 |
| 40 | 9.45300911956197e-05 | 0.000189060182391239 | 0.999905469908804 |
| 41 | 4.29784748029892e-05 | 8.59569496059784e-05 | 0.999957021525197 |
| 42 | 1.68367976950445e-05 | 3.3673595390089e-05 | 0.999983163202305 |
| 43 | 9.1682156103426e-06 | 1.83364312206852e-05 | 0.99999083178439 |
| 44 | 9.71114826857847e-06 | 1.94222965371569e-05 | 0.999990288851731 |
| 45 | 7.81581813158694e-06 | 1.56316362631739e-05 | 0.999992184181868 |
| 46 | 3.50518976565034e-05 | 7.01037953130068e-05 | 0.999964948102343 |
| 47 | 1.48857957188877e-05 | 2.97715914377754e-05 | 0.999985114204281 |
| 48 | 1.86160176362099e-05 | 3.72320352724199e-05 | 0.999981383982364 |
| 49 | 7.97374001049115e-06 | 1.59474800209823e-05 | 0.99999202625999 |
| 50 | 3.96208025974044e-06 | 7.92416051948087e-06 | 0.99999603791974 |
| 51 | 1.18445015597285e-06 | 2.3689003119457e-06 | 0.999998815549844 |
| 52 | 5.85313431602034e-07 | 1.17062686320407e-06 | 0.999999414686568 |
| Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | |||
| Description | # significant tests | % significant tests | OK/NOK |
| 1% type I error level | 26 | 0.742857142857143 | NOK |
| 5% type I error level | 33 | 0.942857142857143 | NOK |
| 10% type I error level | 35 | 1 | NOK |
