Multiple Linear Regression - Estimated Regression Equation |
TVDC [t] = + 6.56847 + 0.546429SK1[t] + 1.14316SK2[t] + 0.0976977SK3[t] + 0.23913SK4[t] + 0.211817SK5[t] + 0.00900298SK6[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) | +6.569 | 1.554 | +4.2260e+00 | 4.028e-05 | 2.014e-05 |
SK1 | +0.5464 | 0.1637 | +3.3380e+00 | 0.001053 | 0.0005264 |
SK2 | +1.143 | 0.1992 | +5.7390e+00 | 4.765e-08 | 2.383e-08 |
SK3 | +0.0977 | 0.1458 | +6.7000e-01 | 0.5038 | 0.2519 |
SK4 | +0.2391 | 0.1995 | +1.1990e+00 | 0.2324 | 0.1162 |
SK5 | +0.2118 | 0.1894 | +1.1180e+00 | 0.2651 | 0.1326 |
SK6 | +0.009003 | 0.1957 | +4.6010e-02 | 0.9634 | 0.4817 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.5548 |
R-squared | 0.3078 |
Adjusted R-squared | 0.2814 |
F-TEST (value) | 11.64 |
F-TEST (DF numerator) | 6 |
F-TEST (DF denominator) | 157 |
p-value | 9.19e-11 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 1.453 |
Sum Squared Residuals | 331.3 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 13 | 13.24 | -0.2438 |
2 | 16 | 15.07 | 0.9252 |
3 | 17 | 15.87 | 1.133 |
4 | 15 | 14.67 | 0.3258 |
5 | 16 | 15.87 | 0.1331 |
6 | 16 | 15.23 | 0.7682 |
7 | 18 | 14.56 | 3.44 |
8 | 16 | 15.11 | 0.8913 |
9 | 17 | 16.92 | 0.07859 |
10 | 17 | 17.02 | -0.01911 |
11 | 17 | 15.57 | 1.426 |
12 | 15 | 15.63 | -0.6278 |
13 | 16 | 15.33 | 0.6727 |
14 | 14 | 13.97 | 0.02546 |
15 | 16 | 15.24 | 0.7595 |
16 | 17 | 15.12 | 1.882 |
17 | 16 | 15.12 | 0.8823 |
18 | 15 | 17.01 | -2.008 |
19 | 17 | 15.77 | 1.231 |
20 | 16 | 14.88 | 1.121 |
21 | 15 | 15.78 | -0.7783 |
22 | 16 | 15.66 | 0.3359 |
23 | 15 | 15.66 | -0.6551 |
24 | 17 | 15.66 | 1.336 |
25 | 14 | 15.01 | -1.011 |
26 | 16 | 14.99 | 1.007 |
27 | 15 | 15.56 | -0.5574 |
28 | 16 | 14.78 | 1.217 |
29 | 16 | 16.1 | -0.1039 |
30 | 13 | 14.51 | -1.512 |
31 | 15 | 17.02 | -2.019 |
32 | 17 | 16.21 | 0.7894 |
33 | 15 | 14.52 | 0.479 |
34 | 13 | 13.63 | -0.6309 |
35 | 17 | 16.51 | 0.4948 |
36 | 15 | 15.11 | -0.1087 |
37 | 14 | 14.28 | -0.2818 |
38 | 14 | 14.32 | -0.3166 |
39 | 18 | 15.66 | 2.345 |
40 | 15 | 16.1 | -1.104 |
41 | 17 | 17.02 | -0.01911 |
42 | 13 | 13.87 | -0.8678 |
43 | 16 | 17.33 | -1.326 |
44 | 15 | 15.96 | -0.9624 |
45 | 15 | 15.33 | -0.3273 |
46 | 16 | 15.56 | 0.4426 |
47 | 15 | 15.8 | -0.8009 |
48 | 13 | 15.77 | -2.769 |
49 | 17 | 16.8 | 0.2017 |
50 | 18 | 17.26 | 0.7366 |
51 | 17 | 17.34 | -0.3447 |
52 | 11 | 14.73 | -3.733 |
53 | 14 | 14.18 | -0.1841 |
54 | 13 | 15.66 | -2.655 |
55 | 15 | 14.56 | 0.4399 |
56 | 17 | 15 | 1.998 |
57 | 16 | 15.53 | 0.4699 |
58 | 15 | 15.77 | -0.7692 |
59 | 17 | 17.37 | -0.3701 |
60 | 16 | 14.69 | 1.315 |
61 | 16 | 15.78 | 0.2217 |
62 | 16 | 14.59 | 1.413 |
63 | 15 | 15.88 | -0.8759 |
64 | 12 | 13.27 | -1.271 |
65 | 17 | 15.52 | 1.479 |
66 | 14 | 15.53 | -1.53 |
67 | 14 | 15.76 | -1.76 |
68 | 16 | 14.99 | 1.007 |
69 | 15 | 14.78 | 0.2191 |
70 | 15 | 17.25 | -2.249 |
71 | 13 | 15.46 | -2.46 |
72 | 13 | 15.56 | -2.557 |
73 | 17 | 16.01 | 0.9916 |
74 | 15 | 14.91 | 0.08669 |
75 | 16 | 15.77 | 0.2308 |
76 | 14 | 15.09 | -1.09 |
77 | 15 | 13.97 | 1.025 |
78 | 17 | 14.51 | 2.488 |
79 | 16 | 15.66 | 0.3359 |
80 | 10 | 13.77 | -3.77 |
81 | 16 | 15.77 | 0.2308 |
82 | 17 | 15.68 | 1.319 |
83 | 17 | 15.78 | 1.222 |
84 | 20 | 16.1 | 3.896 |
85 | 17 | 16.25 | 0.7457 |
86 | 18 | 15.88 | 2.124 |
87 | 15 | 15.12 | -0.1177 |
88 | 17 | 15.01 | 1.989 |
89 | 14 | 12.93 | 1.066 |
90 | 15 | 15.65 | -0.6461 |
91 | 17 | 15.66 | 1.336 |
92 | 16 | 15.77 | 0.2308 |
93 | 17 | 16.9 | 0.09659 |
94 | 15 | 14.99 | 0.007308 |
95 | 16 | 15.66 | 0.3359 |
96 | 18 | 16.02 | 1.985 |
97 | 18 | 16.45 | 1.55 |
98 | 16 | 16.92 | -0.9214 |
99 | 17 | 15.18 | 1.818 |
100 | 15 | 15.66 | -0.6641 |
101 | 13 | 16.11 | -3.113 |
102 | 15 | 14.77 | 0.2281 |
103 | 17 | 16.56 | 0.4362 |
104 | 16 | 15.43 | 0.575 |
105 | 16 | 15.21 | 0.7884 |
106 | 15 | 15.66 | -0.6551 |
107 | 16 | 15.66 | 0.3449 |
108 | 16 | 15.31 | 0.6885 |
109 | 13 | 15.56 | -2.557 |
110 | 15 | 15.33 | -0.3273 |
111 | 12 | 13.85 | -1.85 |
112 | 19 | 15.32 | 3.682 |
113 | 16 | 15.11 | 0.8913 |
114 | 16 | 15.44 | 0.5567 |
115 | 17 | 15.71 | 1.295 |
116 | 16 | 16.42 | -0.4224 |
117 | 14 | 15.55 | -1.548 |
118 | 15 | 15.42 | -0.416 |
119 | 14 | 14.78 | -0.7809 |
120 | 16 | 15.56 | 0.4426 |
121 | 15 | 15.77 | -0.7692 |
122 | 17 | 16.6 | 0.3971 |
123 | 15 | 15.01 | -0.011 |
124 | 16 | 15.32 | 0.6817 |
125 | 16 | 15.57 | 0.4336 |
126 | 15 | 14.67 | 0.3258 |
127 | 15 | 15.31 | -0.3093 |
128 | 11 | 12.25 | -1.246 |
129 | 16 | 15.53 | 0.4699 |
130 | 18 | 16.08 | 1.923 |
131 | 13 | 14.02 | -1.023 |
132 | 11 | 13.87 | -2.868 |
133 | 18 | 17.46 | 0.5412 |
134 | 15 | 16.8 | -1.798 |
135 | 19 | 17.8 | 1.204 |
136 | 17 | 17.02 | -0.01911 |
137 | 13 | 15.33 | -2.327 |
138 | 14 | 15.32 | -1.321 |
139 | 16 | 15.66 | 0.3449 |
140 | 13 | 15.36 | -2.362 |
141 | 17 | 15.68 | 1.319 |
142 | 14 | 15.78 | -1.778 |
143 | 19 | 16.17 | 2.826 |
144 | 14 | 14.51 | -0.512 |
145 | 16 | 15.66 | 0.3449 |
146 | 12 | 13.43 | -1.433 |
147 | 16 | 16.79 | -0.7893 |
148 | 16 | 15.32 | 0.6817 |
149 | 15 | 15.57 | -0.5664 |
150 | 12 | 15.09 | -3.09 |
151 | 15 | 15.66 | -0.6641 |
152 | 17 | 16.41 | 0.5866 |
153 | 13 | 15.44 | -2.443 |
154 | 15 | 13.42 | 1.581 |
155 | 18 | 15.57 | 2.434 |
156 | 15 | 14.4 | 0.604 |
157 | 18 | 15.55 | 2.452 |
158 | 15 | 17.04 | -2.037 |
159 | 15 | 16.01 | -1.006 |
160 | 16 | 15.86 | 0.1353 |
161 | 13 | 13.8 | -0.7956 |
162 | 16 | 15.57 | 0.4336 |
163 | 13 | 15.77 | -2.769 |
164 | 16 | 13.77 | 2.228 |
Goldfeld-Quandt test for Heteroskedasticity | |||
p-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
10 | 0.264 | 0.5279 | 0.736 |
11 | 0.1882 | 0.3764 | 0.8118 |
12 | 0.09787 | 0.1957 | 0.9021 |
13 | 0.05128 | 0.1026 | 0.9487 |
14 | 0.04752 | 0.09505 | 0.9525 |
15 | 0.06466 | 0.1293 | 0.9353 |
16 | 0.07049 | 0.141 | 0.9295 |
17 | 0.04058 | 0.08115 | 0.9594 |
18 | 0.08627 | 0.1725 | 0.9137 |
19 | 0.06037 | 0.1207 | 0.9396 |
20 | 0.04613 | 0.09226 | 0.9539 |
21 | 0.03774 | 0.07548 | 0.9623 |
22 | 0.02296 | 0.04592 | 0.977 |
23 | 0.02368 | 0.04737 | 0.9763 |
24 | 0.02301 | 0.04602 | 0.977 |
25 | 0.07179 | 0.1436 | 0.9282 |
26 | 0.05125 | 0.1025 | 0.9488 |
27 | 0.0435 | 0.087 | 0.9565 |
28 | 0.03058 | 0.06117 | 0.9694 |
29 | 0.02005 | 0.0401 | 0.98 |
30 | 0.02684 | 0.05369 | 0.9732 |
31 | 0.03982 | 0.07963 | 0.9602 |
32 | 0.03766 | 0.07532 | 0.9623 |
33 | 0.0261 | 0.0522 | 0.9739 |
34 | 0.02515 | 0.05031 | 0.9748 |
35 | 0.0179 | 0.03579 | 0.9821 |
36 | 0.01219 | 0.02437 | 0.9878 |
37 | 0.009124 | 0.01825 | 0.9909 |
38 | 0.007572 | 0.01514 | 0.9924 |
39 | 0.02101 | 0.04202 | 0.979 |
40 | 0.01784 | 0.03569 | 0.9822 |
41 | 0.01225 | 0.0245 | 0.9878 |
42 | 0.01307 | 0.02613 | 0.9869 |
43 | 0.01094 | 0.02189 | 0.9891 |
44 | 0.00792 | 0.01584 | 0.9921 |
45 | 0.005961 | 0.01192 | 0.994 |
46 | 0.004039 | 0.008078 | 0.996 |
47 | 0.003609 | 0.007218 | 0.9964 |
48 | 0.01142 | 0.02284 | 0.9886 |
49 | 0.008305 | 0.01661 | 0.9917 |
50 | 0.006573 | 0.01315 | 0.9934 |
51 | 0.00457 | 0.009139 | 0.9954 |
52 | 0.03586 | 0.07172 | 0.9641 |
53 | 0.02711 | 0.05421 | 0.9729 |
54 | 0.05122 | 0.1024 | 0.9488 |
55 | 0.04085 | 0.08171 | 0.9591 |
56 | 0.05086 | 0.1017 | 0.9491 |
57 | 0.04238 | 0.08477 | 0.9576 |
58 | 0.03422 | 0.06844 | 0.9658 |
59 | 0.02623 | 0.05246 | 0.9738 |
60 | 0.02266 | 0.04531 | 0.9773 |
61 | 0.01689 | 0.03379 | 0.9831 |
62 | 0.01612 | 0.03224 | 0.9839 |
63 | 0.01287 | 0.02573 | 0.9871 |
64 | 0.01239 | 0.02479 | 0.9876 |
65 | 0.01496 | 0.02993 | 0.985 |
66 | 0.01595 | 0.03189 | 0.9841 |
67 | 0.01681 | 0.03363 | 0.9832 |
68 | 0.01403 | 0.02805 | 0.986 |
69 | 0.01105 | 0.0221 | 0.989 |
70 | 0.01617 | 0.03235 | 0.9838 |
71 | 0.03592 | 0.07184 | 0.9641 |
72 | 0.0639 | 0.1278 | 0.9361 |
73 | 0.06098 | 0.122 | 0.939 |
74 | 0.05194 | 0.1039 | 0.9481 |
75 | 0.04157 | 0.08315 | 0.9584 |
76 | 0.03838 | 0.07676 | 0.9616 |
77 | 0.03365 | 0.06729 | 0.9664 |
78 | 0.06347 | 0.1269 | 0.9365 |
79 | 0.05149 | 0.103 | 0.9485 |
80 | 0.2037 | 0.4073 | 0.7963 |
81 | 0.1748 | 0.3496 | 0.8252 |
82 | 0.1705 | 0.341 | 0.8295 |
83 | 0.1635 | 0.327 | 0.8365 |
84 | 0.4111 | 0.8223 | 0.5889 |
85 | 0.3769 | 0.7538 | 0.6231 |
86 | 0.4286 | 0.8573 | 0.5714 |
87 | 0.388 | 0.776 | 0.612 |
88 | 0.4389 | 0.8779 | 0.5611 |
89 | 0.4116 | 0.8232 | 0.5884 |
90 | 0.3763 | 0.7525 | 0.6237 |
91 | 0.3756 | 0.7512 | 0.6244 |
92 | 0.3334 | 0.6668 | 0.6666 |
93 | 0.2929 | 0.5858 | 0.7071 |
94 | 0.2566 | 0.5132 | 0.7434 |
95 | 0.2244 | 0.4489 | 0.7756 |
96 | 0.2593 | 0.5187 | 0.7407 |
97 | 0.2727 | 0.5454 | 0.7273 |
98 | 0.2476 | 0.4953 | 0.7524 |
99 | 0.2692 | 0.5383 | 0.7308 |
100 | 0.2371 | 0.4741 | 0.7629 |
101 | 0.3647 | 0.7294 | 0.6353 |
102 | 0.3249 | 0.6498 | 0.6751 |
103 | 0.287 | 0.5739 | 0.713 |
104 | 0.2581 | 0.5162 | 0.7419 |
105 | 0.2293 | 0.4587 | 0.7707 |
106 | 0.1992 | 0.3984 | 0.8008 |
107 | 0.1697 | 0.3394 | 0.8303 |
108 | 0.1459 | 0.2917 | 0.8541 |
109 | 0.203 | 0.406 | 0.797 |
110 | 0.171 | 0.342 | 0.829 |
111 | 0.185 | 0.3701 | 0.815 |
112 | 0.423 | 0.846 | 0.577 |
113 | 0.4061 | 0.8122 | 0.5939 |
114 | 0.3823 | 0.7646 | 0.6177 |
115 | 0.3676 | 0.7351 | 0.6324 |
116 | 0.3303 | 0.6606 | 0.6697 |
117 | 0.3347 | 0.6693 | 0.6653 |
118 | 0.2898 | 0.5796 | 0.7102 |
119 | 0.2556 | 0.5112 | 0.7444 |
120 | 0.2213 | 0.4427 | 0.7787 |
121 | 0.1992 | 0.3984 | 0.8008 |
122 | 0.1776 | 0.3552 | 0.8224 |
123 | 0.1494 | 0.2989 | 0.8506 |
124 | 0.1329 | 0.2659 | 0.8671 |
125 | 0.116 | 0.2321 | 0.884 |
126 | 0.1095 | 0.2189 | 0.8905 |
127 | 0.08565 | 0.1713 | 0.9143 |
128 | 0.08024 | 0.1605 | 0.9198 |
129 | 0.06231 | 0.1246 | 0.9377 |
130 | 0.06552 | 0.131 | 0.9345 |
131 | 0.07264 | 0.1453 | 0.9274 |
132 | 0.145 | 0.29 | 0.855 |
133 | 0.1213 | 0.2427 | 0.8787 |
134 | 0.1034 | 0.2069 | 0.8966 |
135 | 0.08636 | 0.1727 | 0.9136 |
136 | 0.07841 | 0.1568 | 0.9216 |
137 | 0.07551 | 0.151 | 0.9245 |
138 | 0.0664 | 0.1328 | 0.9336 |
139 | 0.04806 | 0.09613 | 0.9519 |
140 | 0.05134 | 0.1027 | 0.9487 |
141 | 0.06094 | 0.1219 | 0.9391 |
142 | 0.05402 | 0.108 | 0.946 |
143 | 0.1046 | 0.2091 | 0.8954 |
144 | 0.1348 | 0.2696 | 0.8652 |
145 | 0.09621 | 0.1924 | 0.9038 |
146 | 0.1006 | 0.2011 | 0.8994 |
147 | 0.07318 | 0.1464 | 0.9268 |
148 | 0.07073 | 0.1415 | 0.9293 |
149 | 0.04455 | 0.08909 | 0.9555 |
150 | 0.03869 | 0.07738 | 0.9613 |
151 | 0.02263 | 0.04527 | 0.9774 |
152 | 0.01248 | 0.02497 | 0.9875 |
153 | 0.1277 | 0.2554 | 0.8723 |
154 | 0.6842 | 0.6316 | 0.3158 |
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | |||
Description | # significant tests | % significant tests | OK/NOK |
1% type I error level | 3 | 0.02069 | NOK |
5% type I error level | 34 | 0.234483 | NOK |
10% type I error level | 58 | 0.4 | NOK |
Ramsey RESET F-Test for powers (2 and 3) of fitted values |
> reset_test_fitted RESET test data: mylm RESET = 1.6445, df1 = 2, df2 = 155, p-value = 0.1965 |
Ramsey RESET F-Test for powers (2 and 3) of regressors |
> reset_test_regressors RESET test data: mylm RESET = 1.2242, df1 = 12, df2 = 145, p-value = 0.2719 |
Ramsey RESET F-Test for powers (2 and 3) of principal components |
> reset_test_principal_components RESET test data: mylm RESET = 0.98483, df1 = 2, df2 = 155, p-value = 0.3758 |
Variance Inflation Factors (Multicollinearity) |
> vif SK1 SK2 SK3 SK4 SK5 SK6 1.088929 1.120502 1.044907 1.041363 1.045446 1.037390 |