Multiple Linear Regression - Estimated Regression Equation |
y[t] = + 5134.77222222222 -467.044444444444`x `[t] -148.627777777778M1[t] -271.844444444445M2[t] + 314.188888888888M3[t] -123.266666666667M4[t] + 70.5166666666663M5[t] + 505.3M6[t] -502.416666666667M7[t] -235.133333333334M8[t] -141.350000000001M9[t] + 157.183333333333M10[t] -492.783333333334M11[t] -5.78333333333334t + 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) | 5134.77222222222 | 307.392995 | 16.7043 | 0 | 0 |
`x ` | -467.044444444444 | 282.083158 | -1.6557 | 0.106986 | 0.053493 |
M1 | -148.627777777778 | 340.191246 | -0.4369 | 0.66495 | 0.332475 |
M2 | -271.844444444445 | 338.817963 | -0.8023 | 0.427934 | 0.213967 |
M3 | 314.188888888888 | 337.745994 | 0.9303 | 0.358799 | 0.179399 |
M4 | -123.266666666667 | 344.278228 | -0.358 | 0.722524 | 0.361262 |
M5 | 70.5166666666663 | 342.013712 | 0.2062 | 0.837879 | 0.41894 |
M6 | 505.3 | 340.038933 | 1.486 | 0.146492 | 0.073246 |
M7 | -502.416666666667 | 338.358964 | -1.4849 | 0.146793 | 0.073397 |
M8 | -235.133333333334 | 336.978214 | -0.6978 | 0.490066 | 0.245033 |
M9 | -141.350000000001 | 335.900374 | -0.4208 | 0.676542 | 0.338271 |
M10 | 157.183333333333 | 335.128365 | 0.469 | 0.642046 | 0.321023 |
M11 | -492.783333333334 | 334.664305 | -1.4725 | 0.150091 | 0.075046 |
t | -5.78333333333334 | 10.178799 | -0.5682 | 0.57365 | 0.286825 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.728609903988344 |
R-squared | 0.530872392189904 |
Adjusted R-squared | 0.351500071556632 |
F-TEST (value) | 2.95961155163553 |
F-TEST (DF numerator) | 13 |
F-TEST (DF denominator) | 34 |
p-value | 0.00554959611353678 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 473.067837374483 |
Sum Squared Residuals | 7608968.07777778 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 4143 | 4980.36111111111 | -837.36111111111 |
2 | 4429 | 4851.36111111111 | -422.361111111112 |
3 | 5219 | 5431.61111111111 | -212.611111111111 |
4 | 4929 | 4988.37222222222 | -59.3722222222223 |
5 | 5761 | 5176.37222222222 | 584.627777777778 |
6 | 5592 | 5605.37222222222 | -13.3722222222220 |
7 | 4163 | 4591.87222222222 | -428.872222222223 |
8 | 4962 | 4853.37222222222 | 108.627777777778 |
9 | 5208 | 4941.37222222222 | 266.627777777778 |
10 | 4755 | 5234.12222222222 | -479.122222222223 |
11 | 4491 | 4578.37222222222 | -87.3722222222222 |
12 | 5732 | 5065.37222222222 | 666.627777777778 |
13 | 5731 | 4910.96111111111 | 820.038888888889 |
14 | 5040 | 4781.96111111111 | 258.038888888889 |
15 | 6102 | 5362.21111111111 | 739.788888888889 |
16 | 4904 | 4918.97222222222 | -14.9722222222223 |
17 | 5369 | 5106.97222222222 | 262.027777777778 |
18 | 5578 | 5535.97222222222 | 42.0277777777776 |
19 | 4619 | 4522.47222222222 | 96.5277777777778 |
20 | 4731 | 4783.97222222222 | -52.9722222222222 |
21 | 5011 | 4871.97222222222 | 139.027777777778 |
22 | 5299 | 5164.72222222222 | 134.277777777777 |
23 | 4146 | 4508.97222222222 | -362.972222222222 |
24 | 4625 | 4995.97222222222 | -370.972222222223 |
25 | 4736 | 4841.56111111111 | -105.561111111112 |
26 | 4219 | 4712.56111111111 | -493.561111111111 |
27 | 5116 | 5292.81111111111 | -176.811111111111 |
28 | 4205 | 4382.52777777778 | -177.527777777778 |
29 | 4121 | 4570.52777777778 | -449.527777777777 |
30 | 5103 | 4999.52777777778 | 103.472222222222 |
31 | 4300 | 3986.02777777778 | 313.972222222223 |
32 | 4578 | 4247.52777777778 | 330.472222222222 |
33 | 3809 | 4335.52777777778 | -526.527777777778 |
34 | 5526 | 4628.27777777778 | 897.722222222222 |
35 | 4248 | 3972.52777777778 | 275.472222222223 |
36 | 3830 | 4459.52777777778 | -629.527777777778 |
37 | 4428 | 4305.11666666667 | 122.883333333333 |
38 | 4834 | 4176.11666666667 | 657.883333333334 |
39 | 4406 | 4756.36666666667 | -350.366666666667 |
40 | 4565 | 4313.12777777778 | 251.872222222222 |
41 | 4104 | 4501.12777777778 | -397.127777777778 |
42 | 4798 | 4930.12777777778 | -132.127777777778 |
43 | 3935 | 3916.62777777778 | 18.3722222222223 |
44 | 3792 | 4178.12777777778 | -386.127777777778 |
45 | 4387 | 4266.12777777778 | 120.872222222222 |
46 | 4006 | 4558.87777777778 | -552.877777777778 |
47 | 4078 | 3903.12777777778 | 174.872222222222 |
48 | 4724 | 4390.12777777778 | 333.872222222222 |
Goldfeld-Quandt test for Heteroskedasticity | |||
p-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
17 | 0.883875062756398 | 0.232249874487204 | 0.116124937243602 |
18 | 0.820568468083745 | 0.35886306383251 | 0.179431531916255 |
19 | 0.70240313208502 | 0.595193735829959 | 0.297596867914979 |
20 | 0.644492898063232 | 0.711014203873536 | 0.355507101936768 |
21 | 0.60673600880083 | 0.78652798239834 | 0.39326399119917 |
22 | 0.49594679375268 | 0.99189358750536 | 0.50405320624732 |
23 | 0.439524626753445 | 0.87904925350689 | 0.560475373246555 |
24 | 0.538612268201938 | 0.922775463596123 | 0.461387731798062 |
25 | 0.433482106602779 | 0.866964213205557 | 0.566517893397221 |
26 | 0.463138269519385 | 0.92627653903877 | 0.536861730480615 |
27 | 0.365284393892662 | 0.730568787785323 | 0.634715606107338 |
28 | 0.277759774759371 | 0.555519549518741 | 0.72224022524063 |
29 | 0.194892447861526 | 0.389784895723053 | 0.805107552138474 |
30 | 0.119376460040273 | 0.238752920080545 | 0.880623539959727 |
31 | 0.0707258272410489 | 0.141451654482098 | 0.929274172758951 |
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 |