| Multiple Linear Regression - Estimated Regression Equation |
| TV4[t] = + 2.66225 -0.0223589IV1[t] + 0.0648903IV3[t] -0.0746503TV1[t] + 0.20264TV3[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) | +2.662 | 0.3986 | +6.6790e+00 | 3.707e-10 | 1.854e-10 |
| IV1 | -0.02236 | 0.04748 | -4.7090e-01 | 0.6384 | 0.3192 |
| IV3 | +0.06489 | 0.0478 | +1.3580e+00 | 0.1765 | 0.08824 |
| TV1 | -0.07465 | 0.06659 | -1.1210e+00 | 0.264 | 0.132 |
| TV3 | +0.2026 | 0.09141 | +2.2170e+00 | 0.02803 | 0.01402 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.2156 |
| R-squared | 0.04647 |
| Adjusted R-squared | 0.02278 |
| F-TEST (value) | 1.962 |
| F-TEST (DF numerator) | 4 |
| F-TEST (DF denominator) | 161 |
| p-value | 0.1029 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 0.5862 |
| Sum Squared Residuals | 55.33 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 3 | 3.122 | -0.1215 |
| 2 | 3 | 3.075 | -0.07501 |
| 3 | 3 | 3.612 | -0.6119 |
| 4 | 3 | 3.344 | -0.3443 |
| 5 | 4 | 3.302 | 0.6982 |
| 6 | 3 | 3.343 | -0.3425 |
| 7 | 5 | 3.539 | 1.461 |
| 8 | 3 | 3.537 | -0.5372 |
| 9 | 4 | 3.56 | 0.4404 |
| 10 | 3 | 3.407 | -0.4074 |
| 11 | 3 | 3.387 | -0.3873 |
| 12 | 3 | 3.215 | -0.2146 |
| 13 | 4 | 3.344 | 0.6557 |
| 14 | 3 | 3.322 | -0.322 |
| 15 | 4 | 3.344 | 0.6557 |
| 16 | 3 | 3.604 | -0.6043 |
| 17 | 4 | 3.259 | 0.7407 |
| 18 | 4 | 3.289 | 0.7108 |
| 19 | 4 | 3.45 | 0.55 |
| 20 | 3 | 3.247 | -0.2473 |
| 21 | 3 | 3.344 | -0.3443 |
| 22 | 3 | 3.402 | -0.4016 |
| 23 | 3 | 3.279 | -0.2794 |
| 24 | 4 | 3.517 | 0.483 |
| 25 | 3 | 3.407 | -0.4074 |
| 26 | 4 | 3.257 | 0.7429 |
| 27 | 3 | 3.302 | -0.3018 |
| 28 | 3 | 3.59 | -0.5895 |
| 29 | 3 | 3.569 | -0.5693 |
| 30 | 3 | 3.194 | -0.194 |
| 31 | 3 | 3.527 | -0.5268 |
| 32 | 4 | 3.272 | 0.7281 |
| 33 | 2 | 3.515 | -1.515 |
| 34 | 3 | 3.279 | -0.2794 |
| 35 | 3 | 3.407 | -0.4074 |
| 36 | 3 | 3.302 | -0.3018 |
| 37 | 4 | 3.462 | 0.5385 |
| 38 | 4 | 3.429 | 0.5713 |
| 39 | 4 | 3.43 | 0.5702 |
| 40 | 3 | 3.279 | -0.2794 |
| 41 | 3 | 3.517 | -0.517 |
| 42 | 3 | 3.099 | -0.09916 |
| 43 | 3 | 3.419 | -0.4194 |
| 44 | 3 | 3.367 | -0.3667 |
| 45 | 3 | 3.644 | -0.644 |
| 46 | 3 | 3.43 | -0.4298 |
| 47 | 3 | 3.344 | -0.3443 |
| 48 | 3 | 3.216 | -0.2163 |
| 49 | 3 | 3.472 | -0.4723 |
| 50 | 3 | 3.472 | -0.4723 |
| 51 | 4 | 3.324 | 0.6758 |
| 52 | 3 | 3.139 | -0.1389 |
| 53 | 3 | 3.441 | -0.4413 |
| 54 | 3 | 3.451 | -0.4511 |
| 55 | 3 | 3.279 | -0.2794 |
| 56 | 3 | 3.205 | -0.2048 |
| 57 | 4 | 3.344 | 0.6557 |
| 58 | 3 | 3.367 | -0.3667 |
| 59 | 3 | 3.407 | -0.4074 |
| 60 | 3 | 3.27 | -0.2697 |
| 61 | 3 | 3.409 | -0.4092 |
| 62 | 3 | 3.14 | -0.1399 |
| 63 | 3 | 3.279 | -0.2794 |
| 64 | 2 | 3.324 | -1.324 |
| 65 | 3 | 3.407 | -0.4074 |
| 66 | 3 | 3.419 | -0.419 |
| 67 | 4 | 3.429 | 0.5713 |
| 68 | 3 | 3.27 | -0.2697 |
| 69 | 3 | 3.279 | -0.2794 |
| 70 | 3 | 3.127 | -0.1273 |
| 71 | 3 | 3.239 | -0.2387 |
| 72 | 3 | 3.324 | -0.3242 |
| 73 | 4 | 3.215 | 0.7854 |
| 74 | 3 | 3.257 | -0.2571 |
| 75 | 3 | 3.407 | -0.4074 |
| 76 | 3 | 3.397 | -0.3966 |
| 77 | 5 | 3.536 | 1.464 |
| 78 | 3 | 3.452 | -0.4521 |
| 79 | 3 | 3.472 | -0.4723 |
| 80 | 3 | 3.236 | -0.2359 |
| 81 | 3 | 3.343 | -0.3425 |
| 82 | 4 | 3.162 | 0.8377 |
| 83 | 4 | 3.407 | 0.5926 |
| 84 | 5 | 3.517 | 1.483 |
| 85 | 4 | 3.46 | 0.5403 |
| 86 | 4 | 3.56 | 0.4404 |
| 87 | 3 | 3.344 | -0.3443 |
| 88 | 4 | 3.314 | 0.6856 |
| 89 | 3 | 2.8 | 0.2005 |
| 90 | 3 | 3.367 | -0.3667 |
| 91 | 3 | 3.504 | -0.5044 |
| 92 | 3 | 3.537 | -0.5372 |
| 93 | 3 | 3.547 | -0.547 |
| 94 | 3 | 3.344 | -0.3443 |
| 95 | 4 | 3.302 | 0.6982 |
| 96 | 5 | 3.344 | 1.656 |
| 97 | 4 | 3.3 | 0.7 |
| 98 | 3 | 3.292 | -0.292 |
| 99 | 4 | 3.472 | 0.5277 |
| 100 | 3 | 3.367 | -0.3667 |
| 101 | 3 | 3.516 | -0.516 |
| 102 | 3 | 3.257 | -0.2571 |
| 103 | 4 | 3.515 | 0.4851 |
| 104 | 4 | 3.279 | 0.7206 |
| 105 | 3 | 3.515 | -0.5149 |
| 106 | 3 | 3.344 | -0.3443 |
| 107 | 4 | 3.344 | 0.6557 |
| 108 | 4 | 3.344 | 0.6557 |
| 109 | 3 | 3.216 | -0.2163 |
| 110 | 3 | 3.302 | -0.3018 |
| 111 | 3 | 3.216 | -0.2163 |
| 112 | 5 | 3.43 | 1.57 |
| 113 | 4 | 3.279 | 0.7206 |
| 114 | 3 | 3.25 | -0.2495 |
| 115 | 4 | 3.475 | 0.5255 |
| 116 | 3 | 3.118 | -0.1175 |
| 117 | 3 | 3.419 | -0.419 |
| 118 | 3 | 3.302 | -0.3018 |
| 119 | 3 | 3.289 | -0.2892 |
| 120 | 4 | 3.344 | 0.6557 |
| 121 | 3 | 3.344 | -0.3443 |
| 122 | 4 | 3.407 | 0.5926 |
| 123 | 3 | 3.389 | -0.3891 |
| 124 | 3 | 3.335 | -0.3346 |
| 125 | 3 | 3.472 | -0.4723 |
| 126 | 3 | 3.344 | -0.3443 |
| 127 | 3 | 3.344 | -0.3443 |
| 128 | 3 | 3.313 | -0.3134 |
| 129 | 4 | 3.344 | 0.6557 |
| 130 | 5 | 3.387 | 1.613 |
| 131 | 3 | 3.259 | -0.2593 |
| 132 | 3 | 3.269 | -0.2686 |
| 133 | 4 | 3.344 | 0.6557 |
| 134 | 5 | 3.634 | 1.366 |
| 135 | 3 | 3.216 | -0.2163 |
| 136 | 3 | 3.389 | -0.3891 |
| 137 | 4 | 3.582 | 0.4181 |
| 138 | 3 | 3.462 | -0.4619 |
| 139 | 3 | 3.344 | -0.3443 |
| 140 | 3 | 3.484 | -0.4839 |
| 141 | 4 | 3.257 | 0.7429 |
| 142 | 3 | 3.239 | -0.2387 |
| 143 | 3 | 3.569 | -0.5693 |
| 144 | 4 | 3.429 | 0.5713 |
| 145 | 4 | 3.537 | 0.4628 |
| 146 | 3 | 3.409 | -0.4092 |
| 147 | 4 | 3.279 | 0.7206 |
| 148 | 3 | 3.087 | -0.08656 |
| 149 | 4 | 3.344 | 0.6557 |
| 150 | 3 | 3.335 | -0.3346 |
| 151 | 3 | 3.324 | -0.3242 |
| 152 | 3 | 3.204 | -0.2037 |
| 153 | 3 | 3.344 | -0.3443 |
| 154 | 3 | 3.407 | -0.4074 |
| 155 | 3 | 3.087 | -0.08656 |
| 156 | 3 | 3.279 | -0.2794 |
| 157 | 4 | 3.407 | 0.5926 |
| 158 | 3 | 3.389 | -0.3891 |
| 159 | 3 | 3.3 | -0.3 |
| 160 | 4 | 3.441 | 0.5587 |
| 161 | 3 | 3.279 | -0.2794 |
| 162 | 4 | 3.279 | 0.7206 |
| 163 | 3 | 3.215 | -0.2146 |
| 164 | 4 | 3.279 | 0.7206 |
| 165 | 3 | 3.174 | -0.1738 |
| 166 | 5 | 3.506 | 1.494 |
| Goldfeld-Quandt test for Heteroskedasticity | |||
| p-values | Alternative Hypothesis | ||
| breakpoint index | greater | 2-sided | less |
| 8 | 0.472 | 0.944 | 0.528 |
| 9 | 0.3769 | 0.7538 | 0.6231 |
| 10 | 0.268 | 0.536 | 0.732 |
| 11 | 0.5855 | 0.8289 | 0.4145 |
| 12 | 0.4866 | 0.9733 | 0.5134 |
| 13 | 0.6052 | 0.7895 | 0.3948 |
| 14 | 0.5089 | 0.9823 | 0.4911 |
| 15 | 0.5441 | 0.9119 | 0.4559 |
| 16 | 0.7366 | 0.5269 | 0.2634 |
| 17 | 0.6931 | 0.6137 | 0.3069 |
| 18 | 0.6397 | 0.7205 | 0.3603 |
| 19 | 0.731 | 0.5381 | 0.269 |
| 20 | 0.6652 | 0.6696 | 0.3348 |
| 21 | 0.6296 | 0.7408 | 0.3704 |
| 22 | 0.5983 | 0.8035 | 0.4017 |
| 23 | 0.5535 | 0.8931 | 0.4465 |
| 24 | 0.5161 | 0.9678 | 0.4839 |
| 25 | 0.4686 | 0.9372 | 0.5314 |
| 26 | 0.5102 | 0.9796 | 0.4898 |
| 27 | 0.4891 | 0.9782 | 0.5109 |
| 28 | 0.4824 | 0.9647 | 0.5176 |
| 29 | 0.4972 | 0.9944 | 0.5028 |
| 30 | 0.444 | 0.888 | 0.556 |
| 31 | 0.4536 | 0.9073 | 0.5464 |
| 32 | 0.445 | 0.8901 | 0.555 |
| 33 | 0.6327 | 0.7346 | 0.3673 |
| 34 | 0.5906 | 0.8188 | 0.4094 |
| 35 | 0.5462 | 0.9076 | 0.4538 |
| 36 | 0.5162 | 0.9676 | 0.4838 |
| 37 | 0.5325 | 0.9351 | 0.4675 |
| 38 | 0.4941 | 0.9882 | 0.5059 |
| 39 | 0.5092 | 0.9817 | 0.4908 |
| 40 | 0.4697 | 0.9393 | 0.5303 |
| 41 | 0.4511 | 0.9022 | 0.5489 |
| 42 | 0.4102 | 0.8204 | 0.5898 |
| 43 | 0.4295 | 0.8591 | 0.5705 |
| 44 | 0.4018 | 0.8037 | 0.5982 |
| 45 | 0.4111 | 0.8222 | 0.5889 |
| 46 | 0.377 | 0.7539 | 0.623 |
| 47 | 0.3423 | 0.6847 | 0.6577 |
| 48 | 0.3103 | 0.6207 | 0.6897 |
| 49 | 0.2821 | 0.5642 | 0.7179 |
| 50 | 0.2561 | 0.5122 | 0.7439 |
| 51 | 0.2613 | 0.5226 | 0.7387 |
| 52 | 0.2325 | 0.4649 | 0.7675 |
| 53 | 0.219 | 0.4379 | 0.781 |
| 54 | 0.2072 | 0.4143 | 0.7928 |
| 55 | 0.1796 | 0.3591 | 0.8204 |
| 56 | 0.1518 | 0.3036 | 0.8482 |
| 57 | 0.1709 | 0.3419 | 0.8291 |
| 58 | 0.1525 | 0.305 | 0.8475 |
| 59 | 0.1346 | 0.2691 | 0.8654 |
| 60 | 0.1138 | 0.2277 | 0.8862 |
| 61 | 0.1002 | 0.2003 | 0.8998 |
| 62 | 0.08162 | 0.1632 | 0.9184 |
| 63 | 0.068 | 0.136 | 0.932 |
| 64 | 0.1771 | 0.3543 | 0.8229 |
| 65 | 0.1597 | 0.3195 | 0.8403 |
| 66 | 0.1439 | 0.2878 | 0.8561 |
| 67 | 0.148 | 0.2961 | 0.852 |
| 68 | 0.1271 | 0.2542 | 0.8729 |
| 69 | 0.1088 | 0.2175 | 0.8912 |
| 70 | 0.0894 | 0.1788 | 0.9106 |
| 71 | 0.07563 | 0.1513 | 0.9244 |
| 72 | 0.06521 | 0.1304 | 0.9348 |
| 73 | 0.08104 | 0.1621 | 0.919 |
| 74 | 0.06777 | 0.1356 | 0.9322 |
| 75 | 0.06057 | 0.1211 | 0.9394 |
| 76 | 0.05329 | 0.1066 | 0.9467 |
| 77 | 0.1775 | 0.3549 | 0.8225 |
| 78 | 0.1668 | 0.3337 | 0.8332 |
| 79 | 0.161 | 0.3219 | 0.839 |
| 80 | 0.148 | 0.296 | 0.852 |
| 81 | 0.1363 | 0.2726 | 0.8637 |
| 82 | 0.1671 | 0.3342 | 0.8329 |
| 83 | 0.1757 | 0.3513 | 0.8243 |
| 84 | 0.3888 | 0.7776 | 0.6112 |
| 85 | 0.3839 | 0.7679 | 0.6161 |
| 86 | 0.369 | 0.738 | 0.631 |
| 87 | 0.3431 | 0.6862 | 0.6569 |
| 88 | 0.3615 | 0.723 | 0.6385 |
| 89 | 0.3291 | 0.6581 | 0.6709 |
| 90 | 0.3037 | 0.6074 | 0.6963 |
| 91 | 0.3031 | 0.6062 | 0.6969 |
| 92 | 0.3153 | 0.6305 | 0.6847 |
| 93 | 0.3398 | 0.6796 | 0.6602 |
| 94 | 0.3173 | 0.6345 | 0.6827 |
| 95 | 0.3377 | 0.6754 | 0.6623 |
| 96 | 0.6506 | 0.6987 | 0.3494 |
| 97 | 0.6599 | 0.6801 | 0.3401 |
| 98 | 0.6246 | 0.7509 | 0.3754 |
| 99 | 0.6087 | 0.7827 | 0.3913 |
| 100 | 0.5817 | 0.8366 | 0.4183 |
| 101 | 0.5896 | 0.8208 | 0.4104 |
| 102 | 0.5595 | 0.881 | 0.4405 |
| 103 | 0.5394 | 0.9212 | 0.4606 |
| 104 | 0.5594 | 0.8813 | 0.4406 |
| 105 | 0.6237 | 0.7526 | 0.3763 |
| 106 | 0.6049 | 0.7901 | 0.3951 |
| 107 | 0.6062 | 0.7876 | 0.3938 |
| 108 | 0.6076 | 0.7849 | 0.3924 |
| 109 | 0.5639 | 0.8722 | 0.4361 |
| 110 | 0.5262 | 0.9476 | 0.4738 |
| 111 | 0.4808 | 0.9617 | 0.5192 |
| 112 | 0.7331 | 0.5337 | 0.2669 |
| 113 | 0.7537 | 0.4927 | 0.2463 |
| 114 | 0.7173 | 0.5655 | 0.2827 |
| 115 | 0.7352 | 0.5295 | 0.2648 |
| 116 | 0.6931 | 0.6138 | 0.3069 |
| 117 | 0.7036 | 0.5929 | 0.2964 |
| 118 | 0.6639 | 0.6723 | 0.3361 |
| 119 | 0.6368 | 0.7264 | 0.3632 |
| 120 | 0.6376 | 0.7247 | 0.3624 |
| 121 | 0.6166 | 0.7669 | 0.3834 |
| 122 | 0.5974 | 0.8051 | 0.4026 |
| 123 | 0.5547 | 0.8906 | 0.4453 |
| 124 | 0.5238 | 0.9523 | 0.4762 |
| 125 | 0.562 | 0.8759 | 0.438 |
| 126 | 0.548 | 0.904 | 0.452 |
| 127 | 0.5371 | 0.9258 | 0.4629 |
| 128 | 0.4932 | 0.9864 | 0.5068 |
| 129 | 0.4809 | 0.9617 | 0.5191 |
| 130 | 0.7029 | 0.5942 | 0.2971 |
| 131 | 0.6537 | 0.6926 | 0.3463 |
| 132 | 0.6477 | 0.7045 | 0.3523 |
| 133 | 0.6429 | 0.7142 | 0.3571 |
| 134 | 0.7725 | 0.455 | 0.2275 |
| 135 | 0.7313 | 0.5374 | 0.2687 |
| 136 | 0.687 | 0.626 | 0.313 |
| 137 | 0.673 | 0.6539 | 0.327 |
| 138 | 0.6425 | 0.7151 | 0.3575 |
| 139 | 0.612 | 0.7759 | 0.388 |
| 140 | 0.6935 | 0.6131 | 0.3065 |
| 141 | 0.6946 | 0.6107 | 0.3054 |
| 142 | 0.6391 | 0.7219 | 0.3609 |
| 143 | 0.7762 | 0.4476 | 0.2238 |
| 144 | 0.7528 | 0.4945 | 0.2472 |
| 145 | 0.6927 | 0.6145 | 0.3073 |
| 146 | 0.7351 | 0.5298 | 0.2649 |
| 147 | 0.7692 | 0.4616 | 0.2308 |
| 148 | 0.715 | 0.5699 | 0.285 |
| 149 | 0.7 | 0.6 | 0.3 |
| 150 | 0.6209 | 0.7581 | 0.3791 |
| 151 | 0.5429 | 0.9141 | 0.4571 |
| 152 | 0.6847 | 0.6307 | 0.3153 |
| 153 | 0.6962 | 0.6076 | 0.3038 |
| 154 | 0.7748 | 0.4503 | 0.2252 |
| 155 | 0.68 | 0.6399 | 0.32 |
| 156 | 0.6996 | 0.6008 | 0.3004 |
| 157 | 0.5594 | 0.8811 | 0.4406 |
| 158 | 0.5562 | 0.8877 | 0.4438 |
| 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 |
| Ramsey RESET F-Test for powers (2 and 3) of fitted values |
> reset_test_fitted RESET test data: mylm RESET = 0.10386, df1 = 2, df2 = 159, p-value = 0.9014 |
| Ramsey RESET F-Test for powers (2 and 3) of regressors |
> reset_test_regressors RESET test data: mylm RESET = 0.72891, df1 = 8, df2 = 153, p-value = 0.6658 |
| Ramsey RESET F-Test for powers (2 and 3) of principal components |
> reset_test_principal_components RESET test data: mylm RESET = 2.2241, df1 = 2, df2 = 159, p-value = 0.1115 |
| Variance Inflation Factors (Multicollinearity) |
> vif
IV1 IV3 TV1 TV3
1.052865 1.020194 1.614666 1.615232
|
