Multiple Linear Regression - Estimated Regression Equation |
Prod[t] = + 799.47445598441 -2.26997272111808Werkl[t] -15.4298983271748M1[t] -10.0415966195063M2[t] + 18.0761867894057M3[t] -57.1149074568893M4[t] -58.290902316463M5[t] -25.2285475961726M6[t] -51.937549094269M7[t] -42.6129379524887M8[t] -17.4585723206456M9[t] -24.3548984374369M10[t] -16.9687985934948M11[t] + 1.60916321607065t + 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) | 799.47445598441 | 84.595798 | 9.4505 | 0 | 0 |
Werkl | -2.26997272111808 | 0.653062 | -3.4759 | 0.001122 | 0.000561 |
M1 | -15.4298983271748 | 19.689126 | -0.7837 | 0.437247 | 0.218623 |
M2 | -10.0415966195063 | 20.6679 | -0.4859 | 0.629377 | 0.314688 |
M3 | 18.0761867894057 | 15.609322 | 1.158 | 0.252826 | 0.126413 |
M4 | -57.1149074568893 | 17.959417 | -3.1802 | 0.002634 | 0.001317 |
M5 | -58.290902316463 | 17.552113 | -3.321 | 0.001763 | 0.000881 |
M6 | -25.2285475961726 | 15.385714 | -1.6397 | 0.107882 | 0.053941 |
M7 | -51.937549094269 | 18.52223 | -2.8041 | 0.007367 | 0.003683 |
M8 | -42.6129379524887 | 18.163789 | -2.346 | 0.023339 | 0.01167 |
M9 | -17.4585723206456 | 15.609036 | -1.1185 | 0.269164 | 0.134582 |
M10 | -24.3548984374369 | 15.813885 | -1.5401 | 0.130389 | 0.065194 |
M11 | -16.9687985934948 | 15.263641 | -1.1117 | 0.272038 | 0.136019 |
t | 1.60916321607065 | 0.184038 | 8.7437 | 0 | 0 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.860766387238483 |
R-squared | 0.74091877339959 |
Adjusted R-squared | 0.667700165882082 |
F-TEST (value) | 10.1192688378078 |
F-TEST (DF numerator) | 13 |
F-TEST (DF denominator) | 46 |
p-value | 1.47951073614649e-09 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 24.0872167020129 |
Sum Squared Residuals | 26688.9243886876 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 581 | 550.711544237585 | 30.2884557624147 |
2 | 597 | 555.212039168093 | 41.7879608319066 |
3 | 587 | 553.159367697423 | 33.8406323025773 |
4 | 536 | 507.498101136951 | 28.5018988630492 |
5 | 524 | 497.943389520528 | 26.0566104794718 |
6 | 537 | 507.872204796702 | 29.1277952032979 |
7 | 536 | 515.913968243 | 20.0860317569997 |
8 | 533 | 525.48575896818 | 7.51424103181953 |
9 | 528 | 511.389778835969 | 16.6102211640312 |
10 | 516 | 533.569285860777 | -17.5692858607769 |
11 | 502 | 506.925977199236 | -4.92597719923579 |
12 | 506 | 521.6449853829 | -15.6449853829003 |
13 | 518 | 567.29753556509 | -49.2975355650901 |
14 | 534 | 550.460286917089 | -16.4602869170893 |
15 | 528 | 559.076487235674 | -31.0764872356738 |
16 | 478 | 513.18822340309 | -35.1882234030901 |
17 | 469 | 479.117806398592 | -10.1178063985922 |
18 | 490 | 529.452136110668 | -39.452136110668 |
19 | 493 | 511.389213264108 | -18.3892132641082 |
20 | 508 | 521.868993077736 | -13.8689930777356 |
21 | 517 | 542.50359557863 | -25.5035955786305 |
22 | 514 | 526.774558160767 | -12.7745581607668 |
23 | 510 | 520.7880012614 | -10.7880012614002 |
24 | 527 | 563.200676642706 | -36.2006766427055 |
25 | 542 | 565.042753307316 | -23.0427533073161 |
26 | 565 | 576.807160945403 | -11.8071609454033 |
27 | 555 | 572.711514025726 | -17.7115140257264 |
28 | 499 | 522.283304750906 | -23.2833047509065 |
29 | 511 | 533.61234216877 | -22.6123421687703 |
30 | 526 | 528.105342941341 | -2.10534294134123 |
31 | 532 | 539.552065469317 | -7.55206546931661 |
32 | 549 | 545.71889711282 | 3.2811028871804 |
33 | 561 | 563.856529620485 | -2.85652962048465 |
34 | 557 | 544.26853857672 | 12.7314614232799 |
35 | 566 | 544.637905296484 | 21.3620947035158 |
36 | 588 | 566.847823459838 | 21.1521765401615 |
37 | 620 | 587.530673709729 | 32.4693262902708 |
38 | 626 | 619.951833109991 | 6.04816689000898 |
39 | 620 | 599.05838805404 | 20.9416119459597 |
40 | 573 | 537.053317901518 | 35.9466820984818 |
41 | 573 | 559.50522165286 | 13.4947783471394 |
42 | 574 | 545.372326085183 | 28.6276739148172 |
43 | 580 | 561.585991327506 | 18.4140086724939 |
44 | 590 | 575.697727494922 | 14.3022725050776 |
45 | 593 | 590.657398193022 | 2.34260180697787 |
46 | 597 | 577.198333496276 | 19.8016665037235 |
47 | 595 | 592.095525631196 | 2.90447436880373 |
48 | 612 | 587.746762957469 | 24.2532370425310 |
49 | 628 | 618.417493180279 | 9.58250681972072 |
50 | 629 | 648.568679859423 | -19.568679859423 |
51 | 621 | 626.994242987137 | -5.99424298713684 |
52 | 569 | 574.977052807534 | -5.97705280753435 |
53 | 567 | 573.821240259249 | -6.82124025924866 |
54 | 573 | 589.197990066106 | -16.1979900661059 |
55 | 584 | 596.558761696069 | -12.5587616960688 |
56 | 589 | 600.228623346342 | -11.2286233463419 |
57 | 591 | 581.592697771894 | 9.40730222810607 |
58 | 595 | 597.18928390546 | -2.18928390545971 |
59 | 594 | 602.552590611684 | -8.55259061168358 |
60 | 611 | 604.559751557087 | 6.4402484429131 |
Goldfeld-Quandt test for Heteroskedasticity | |||
p-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
17 | 0.00276615110530828 | 0.00553230221061656 | 0.997233848894692 |
18 | 0.0088351617559298 | 0.0176703235118596 | 0.99116483824407 |
19 | 0.0113262339583846 | 0.0226524679167692 | 0.988673766041615 |
20 | 0.0626069488962769 | 0.125213897792554 | 0.937393051103723 |
21 | 0.154997669756010 | 0.309995339512020 | 0.84500233024399 |
22 | 0.382506820972940 | 0.765013641945879 | 0.61749317902706 |
23 | 0.550748673972011 | 0.898502652055979 | 0.449251326027989 |
24 | 0.625983248459461 | 0.748033503081078 | 0.374016751540539 |
25 | 0.831996172803434 | 0.336007654393133 | 0.168003827196566 |
26 | 0.84337821870609 | 0.313243562587821 | 0.156621781293910 |
27 | 0.883752520257794 | 0.232494959484413 | 0.116247479742206 |
28 | 0.950361350794665 | 0.0992772984106707 | 0.0496386492053354 |
29 | 0.972067781698 | 0.0558644366039987 | 0.0279322183019994 |
30 | 0.98721884875114 | 0.0255623024977191 | 0.0127811512488595 |
31 | 0.995213219082117 | 0.00957356183576684 | 0.00478678091788342 |
32 | 0.998007392191113 | 0.00398521561777478 | 0.00199260780888739 |
33 | 0.99874105383356 | 0.00251789233288183 | 0.00125894616644092 |
34 | 0.999921531227765 | 0.000156937544470867 | 7.84687722354333e-05 |
35 | 0.999990069420069 | 1.98611598630301e-05 | 9.93057993151506e-06 |
36 | 0.999999995338942 | 9.32211631474562e-09 | 4.66105815737281e-09 |
37 | 0.99999999860192 | 2.79616176650075e-09 | 1.39808088325037e-09 |
38 | 0.999999991341513 | 1.73169750771443e-08 | 8.65848753857217e-09 |
39 | 0.999999915551844 | 1.68896312635276e-07 | 8.44481563176382e-08 |
40 | 0.999999593326704 | 8.13346592182642e-07 | 4.06673296091321e-07 |
41 | 0.999999005113444 | 1.98977311308084e-06 | 9.94886556540421e-07 |
42 | 0.999990699265017 | 1.86014699657421e-05 | 9.30073498287107e-06 |
43 | 0.999996244643348 | 7.51071330340949e-06 | 3.75535665170474e-06 |
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | |||
Description | # significant tests | % significant tests | OK/NOK |
1% type I error level | 14 | 0.518518518518518 | NOK |
5% type I error level | 17 | 0.62962962962963 | NOK |
10% type I error level | 19 | 0.703703703703704 | NOK |