Multiple Linear Regression - Estimated Regression Equation |
TVSUM[t] = + 7.63641 + 0.508377SK1[t] + 1.10968SK2[t] + 0.393957SK4[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) | +7.636 | 1.011 | +7.5540e+00 | 2.989e-12 | 1.494e-12 |
SK1 | +0.5084 | 0.1573 | +3.2320e+00 | 0.00149 | 0.0007449 |
SK2 | +1.11 | 0.1895 | +5.8560e+00 | 2.591e-08 | 1.295e-08 |
SK4 | +0.394 | 0.2027 | +1.9440e+00 | 0.05366 | 0.02683 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.5525 |
R-squared | 0.3052 |
Adjusted R-squared | 0.2923 |
F-TEST (value) | 23.58 |
F-TEST (DF numerator) | 3 |
F-TEST (DF denominator) | 161 |
p-value | 1.056e-12 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 1.395 |
Sum Squared Residuals | 313.4 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 13 | 13.07 | -0.07114 |
2 | 16 | 15.08 | 0.9168 |
3 | 17 | 15.68 | 1.316 |
4 | 15 | 14.78 | 0.2179 |
5 | 16 | 15.68 | 0.3155 |
6 | 16 | 15.18 | 0.8239 |
7 | 17 | 14.78 | 2.218 |
8 | 16 | 15.18 | 0.8239 |
9 | 17 | 16.79 | 0.2059 |
10 | 17 | 16.79 | 0.2059 |
11 | 17 | 15.68 | 1.316 |
12 | 15 | 15.29 | -0.2905 |
13 | 16 | 15.29 | 0.7095 |
14 | 14 | 14.07 | -0.0664 |
15 | 16 | 15.68 | 0.3155 |
16 | 17 | 15.18 | 1.824 |
17 | 16 | 15.18 | 0.8239 |
18 | 15 | 16.91 | -1.909 |
19 | 17 | 15.68 | 1.316 |
20 | 16 | 14.78 | 1.218 |
21 | 15 | 15.68 | -0.6845 |
22 | 16 | 15.68 | 0.3155 |
23 | 15 | 15.68 | -0.6845 |
24 | 17 | 15.68 | 1.316 |
25 | 15 | 15.18 | -0.1761 |
26 | 16 | 14.78 | 1.218 |
27 | 15 | 15.68 | -0.6845 |
28 | 16 | 14.67 | 1.332 |
29 | 16 | 16.19 | -0.1928 |
30 | 13 | 14.57 | -1.575 |
31 | 15 | 16.79 | -1.794 |
32 | 17 | 16.19 | 0.8072 |
33 | 15 | 14.57 | 0.4252 |
34 | 13 | 13.56 | -0.558 |
35 | 17 | 16.79 | 0.2059 |
36 | 15 | 15.18 | -0.1761 |
37 | 14 | 14.18 | -0.1808 |
38 | 14 | 14.57 | -0.5748 |
39 | 18 | 15.68 | 2.316 |
40 | 15 | 16.19 | -1.193 |
41 | 17 | 16.79 | 0.2059 |
42 | 13 | 14.07 | -1.066 |
43 | 16 | 16.91 | -0.9085 |
44 | 15 | 15.8 | -0.7989 |
45 | 15 | 15.29 | -0.2905 |
46 | 16 | 15.68 | 0.3155 |
47 | 15 | 15.89 | -0.8918 |
48 | 13 | 15.68 | -2.684 |
49 | 17 | 16.79 | 0.2059 |
50 | 17 | 17.3 | -0.3025 |
51 | 17 | 17.3 | -0.3025 |
52 | 11 | 14.57 | -3.575 |
53 | 14 | 14.18 | -0.1808 |
54 | 13 | 15.68 | -2.684 |
55 | 15 | 14.78 | 0.2179 |
56 | 17 | 15.18 | 1.824 |
57 | 16 | 15.29 | 0.7095 |
58 | 15 | 15.68 | -0.6845 |
59 | 17 | 17.3 | -0.3025 |
60 | 16 | 14.67 | 1.332 |
61 | 16 | 15.68 | 0.3155 |
62 | 16 | 15.18 | 0.8239 |
63 | 15 | 15.68 | -0.6845 |
64 | 12 | 13.47 | -1.465 |
65 | 17 | 15.29 | 1.71 |
66 | 14 | 15.29 | -1.29 |
67 | 14 | 15.8 | -1.799 |
68 | 16 | 14.78 | 1.218 |
69 | 15 | 14.78 | 0.2179 |
70 | 15 | 17.19 | -2.188 |
71 | 13 | 15.68 | -2.684 |
72 | 13 | 15.68 | -2.684 |
73 | 17 | 16.08 | 0.9216 |
74 | 15 | 15.18 | -0.1761 |
75 | 16 | 15.68 | 0.3155 |
76 | 14 | 14.78 | -0.7821 |
77 | 15 | 14.07 | 0.9336 |
78 | 17 | 14.57 | 2.425 |
79 | 16 | 15.68 | 0.3155 |
80 | 12 | 14.07 | -2.066 |
81 | 16 | 15.68 | 0.3155 |
82 | 17 | 15.68 | 1.316 |
83 | 17 | 15.68 | 1.316 |
84 | 20 | 16.19 | 3.807 |
85 | 17 | 16.59 | 0.4132 |
86 | 18 | 15.68 | 2.316 |
87 | 15 | 15.18 | -0.1761 |
88 | 17 | 15.18 | 1.824 |
89 | 14 | 13.07 | 0.9289 |
90 | 15 | 15.68 | -0.6845 |
91 | 17 | 15.68 | 1.316 |
92 | 16 | 15.68 | 0.3155 |
93 | 17 | 16.79 | 0.2059 |
94 | 15 | 14.78 | 0.2179 |
95 | 16 | 15.68 | 0.3155 |
96 | 18 | 16.19 | 1.807 |
97 | 18 | 16.59 | 1.413 |
98 | 16 | 16.79 | -0.7941 |
99 | 17 | 15.08 | 1.917 |
100 | 15 | 15.68 | -0.6845 |
101 | 13 | 16.19 | -3.193 |
102 | 15 | 14.78 | 0.2179 |
103 | 17 | 16.59 | 0.4132 |
104 | 16 | 15.29 | 0.7095 |
105 | 16 | 15.29 | 0.7095 |
106 | 15 | 15.68 | -0.6845 |
107 | 16 | 15.68 | 0.3155 |
108 | 16 | 15.18 | 0.8239 |
109 | 13 | 15.68 | -2.684 |
110 | 15 | 15.29 | -0.2905 |
111 | 12 | 13.67 | -1.672 |
112 | 19 | 15.29 | 3.71 |
113 | 16 | 15.18 | 0.8239 |
114 | 16 | 15.68 | 0.3155 |
115 | 17 | 16.59 | 0.4132 |
116 | 16 | 16.19 | -0.1928 |
117 | 14 | 15.68 | -1.684 |
118 | 15 | 15.29 | -0.2905 |
119 | 14 | 14.78 | -0.7821 |
120 | 16 | 15.68 | 0.3155 |
121 | 15 | 15.68 | -0.6845 |
122 | 17 | 16.79 | 0.2059 |
123 | 15 | 15.18 | -0.1761 |
124 | 16 | 15.29 | 0.7095 |
125 | 16 | 15.68 | 0.3155 |
126 | 15 | 14.78 | 0.2179 |
127 | 15 | 15.29 | -0.2905 |
128 | 11 | 12.17 | -1.169 |
129 | 16 | 15.29 | 0.7095 |
130 | 18 | 15.8 | 2.201 |
131 | 13 | 14.27 | -1.274 |
132 | 11 | 14.07 | -3.066 |
133 | 16 | 15.29 | 0.7095 |
134 | 18 | 17.3 | 0.6975 |
135 | 15 | 16.79 | -1.794 |
136 | 19 | 17.7 | 1.304 |
137 | 17 | 16.79 | 0.2059 |
138 | 13 | 15.29 | -2.29 |
139 | 14 | 15.18 | -1.176 |
140 | 16 | 15.68 | 0.3155 |
141 | 13 | 15.68 | -2.684 |
142 | 17 | 15.68 | 1.316 |
143 | 14 | 15.68 | -1.684 |
144 | 19 | 15.8 | 3.201 |
145 | 14 | 14.57 | -0.5748 |
146 | 16 | 15.68 | 0.3155 |
147 | 12 | 13.67 | -1.672 |
148 | 16 | 16.79 | -0.7941 |
149 | 16 | 15.29 | 0.7095 |
150 | 15 | 15.68 | -0.6845 |
151 | 12 | 14.78 | -2.782 |
152 | 15 | 15.68 | -0.6845 |
153 | 17 | 16.19 | 0.8072 |
154 | 13 | 15.68 | -2.684 |
155 | 15 | 13.56 | 1.442 |
156 | 18 | 15.68 | 2.316 |
157 | 15 | 14.18 | 0.8192 |
158 | 18 | 15.68 | 2.316 |
159 | 15 | 17.19 | -2.188 |
160 | 15 | 16.19 | -1.193 |
161 | 16 | 15.8 | 0.2011 |
162 | 13 | 14.07 | -1.066 |
163 | 16 | 15.68 | 0.3155 |
164 | 13 | 15.68 | -2.684 |
165 | 16 | 13.95 | 2.048 |
Goldfeld-Quandt test for Heteroskedasticity | |||
p-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
7 | 0.2862 | 0.5724 | 0.7138 |
8 | 0.1504 | 0.3008 | 0.8496 |
9 | 0.13 | 0.2601 | 0.87 |
10 | 0.07769 | 0.1554 | 0.9223 |
11 | 0.05117 | 0.1023 | 0.9488 |
12 | 0.03429 | 0.06858 | 0.9657 |
13 | 0.01881 | 0.03763 | 0.9812 |
14 | 0.01666 | 0.03333 | 0.9833 |
15 | 0.008611 | 0.01722 | 0.9914 |
16 | 0.008582 | 0.01716 | 0.9914 |
17 | 0.004281 | 0.008563 | 0.9957 |
18 | 0.01095 | 0.0219 | 0.9891 |
19 | 0.008141 | 0.01628 | 0.9919 |
20 | 0.005352 | 0.0107 | 0.9946 |
21 | 0.006326 | 0.01265 | 0.9937 |
22 | 0.003493 | 0.006987 | 0.9965 |
23 | 0.003614 | 0.007229 | 0.9964 |
24 | 0.003067 | 0.006134 | 0.9969 |
25 | 0.003455 | 0.00691 | 0.9965 |
26 | 0.002264 | 0.004527 | 0.9977 |
27 | 0.002124 | 0.004247 | 0.9979 |
28 | 0.001313 | 0.002626 | 0.9987 |
29 | 0.00072 | 0.00144 | 0.9993 |
30 | 0.002254 | 0.004509 | 0.9977 |
31 | 0.005583 | 0.01117 | 0.9944 |
32 | 0.00573 | 0.01146 | 0.9943 |
33 | 0.003591 | 0.007183 | 0.9964 |
34 | 0.006053 | 0.01211 | 0.9939 |
35 | 0.003847 | 0.007694 | 0.9962 |
36 | 0.002841 | 0.005682 | 0.9972 |
37 | 0.001872 | 0.003744 | 0.9981 |
38 | 0.001369 | 0.002737 | 0.9986 |
39 | 0.00395 | 0.0079 | 0.996 |
40 | 0.003537 | 0.007075 | 0.9965 |
41 | 0.002273 | 0.004546 | 0.9977 |
42 | 0.002835 | 0.00567 | 0.9972 |
43 | 0.002247 | 0.004494 | 0.9978 |
44 | 0.00159 | 0.00318 | 0.9984 |
45 | 0.001044 | 0.002088 | 0.999 |
46 | 0.0006588 | 0.001318 | 0.9993 |
47 | 0.0006996 | 0.001399 | 0.9993 |
48 | 0.004084 | 0.008168 | 0.9959 |
49 | 0.002749 | 0.005498 | 0.9973 |
50 | 0.001827 | 0.003654 | 0.9982 |
51 | 0.001199 | 0.002399 | 0.9988 |
52 | 0.01536 | 0.03072 | 0.9846 |
53 | 0.0111 | 0.0222 | 0.9889 |
54 | 0.02896 | 0.05793 | 0.971 |
55 | 0.02184 | 0.04369 | 0.9782 |
56 | 0.02526 | 0.05051 | 0.9747 |
57 | 0.02064 | 0.04127 | 0.9794 |
58 | 0.01633 | 0.03267 | 0.9837 |
59 | 0.01207 | 0.02413 | 0.9879 |
60 | 0.01074 | 0.02147 | 0.9893 |
61 | 0.007941 | 0.01588 | 0.9921 |
62 | 0.006222 | 0.01244 | 0.9938 |
63 | 0.004775 | 0.00955 | 0.9952 |
64 | 0.004702 | 0.009403 | 0.9953 |
65 | 0.006021 | 0.01204 | 0.994 |
66 | 0.006117 | 0.01223 | 0.9939 |
67 | 0.007261 | 0.01452 | 0.9927 |
68 | 0.006466 | 0.01293 | 0.9935 |
69 | 0.004825 | 0.009649 | 0.9952 |
70 | 0.008075 | 0.01615 | 0.9919 |
71 | 0.0192 | 0.0384 | 0.9808 |
72 | 0.04016 | 0.08032 | 0.9598 |
73 | 0.0393 | 0.0786 | 0.9607 |
74 | 0.03142 | 0.06285 | 0.9686 |
75 | 0.02494 | 0.04987 | 0.9751 |
76 | 0.02277 | 0.04554 | 0.9772 |
77 | 0.01968 | 0.03935 | 0.9803 |
78 | 0.03967 | 0.07935 | 0.9603 |
79 | 0.03159 | 0.06319 | 0.9684 |
80 | 0.04592 | 0.09184 | 0.9541 |
81 | 0.03684 | 0.07367 | 0.9632 |
82 | 0.03751 | 0.07503 | 0.9625 |
83 | 0.038 | 0.076 | 0.962 |
84 | 0.1701 | 0.3402 | 0.8299 |
85 | 0.1479 | 0.2958 | 0.8521 |
86 | 0.2006 | 0.4011 | 0.7994 |
87 | 0.1729 | 0.3458 | 0.8271 |
88 | 0.2017 | 0.4035 | 0.7983 |
89 | 0.1831 | 0.3662 | 0.8169 |
90 | 0.1606 | 0.3212 | 0.8394 |
91 | 0.159 | 0.318 | 0.841 |
92 | 0.1346 | 0.2692 | 0.8654 |
93 | 0.1128 | 0.2256 | 0.8872 |
94 | 0.09511 | 0.1902 | 0.9049 |
95 | 0.07836 | 0.1567 | 0.9216 |
96 | 0.08976 | 0.1795 | 0.9102 |
97 | 0.08974 | 0.1795 | 0.9103 |
98 | 0.07696 | 0.1539 | 0.923 |
99 | 0.09056 | 0.1811 | 0.9094 |
100 | 0.07665 | 0.1533 | 0.9233 |
101 | 0.1765 | 0.3531 | 0.8235 |
102 | 0.1514 | 0.3028 | 0.8486 |
103 | 0.1274 | 0.2548 | 0.8726 |
104 | 0.1104 | 0.2208 | 0.8896 |
105 | 0.09514 | 0.1903 | 0.9049 |
106 | 0.0804 | 0.1608 | 0.9196 |
107 | 0.06537 | 0.1307 | 0.9346 |
108 | 0.0605 | 0.121 | 0.9395 |
109 | 0.1038 | 0.2077 | 0.8962 |
110 | 0.0846 | 0.1692 | 0.9154 |
111 | 0.08858 | 0.1772 | 0.9114 |
112 | 0.2677 | 0.5353 | 0.7323 |
113 | 0.2592 | 0.5184 | 0.7408 |
114 | 0.2245 | 0.4489 | 0.7755 |
115 | 0.191 | 0.3821 | 0.809 |
116 | 0.1625 | 0.3251 | 0.8375 |
117 | 0.1719 | 0.3438 | 0.8281 |
118 | 0.1426 | 0.2852 | 0.8574 |
119 | 0.1204 | 0.2408 | 0.8796 |
120 | 0.09858 | 0.1972 | 0.9014 |
121 | 0.08191 | 0.1638 | 0.9181 |
122 | 0.0664 | 0.1328 | 0.9336 |
123 | 0.05328 | 0.1066 | 0.9467 |
124 | 0.04477 | 0.08953 | 0.9552 |
125 | 0.0346 | 0.0692 | 0.9654 |
126 | 0.02931 | 0.05861 | 0.9707 |
127 | 0.02166 | 0.04332 | 0.9783 |
128 | 0.01887 | 0.03773 | 0.9811 |
129 | 0.01538 | 0.03076 | 0.9846 |
130 | 0.02121 | 0.04242 | 0.9788 |
131 | 0.01744 | 0.03489 | 0.9826 |
132 | 0.04584 | 0.09168 | 0.9542 |
133 | 0.04135 | 0.08271 | 0.9586 |
134 | 0.03509 | 0.07018 | 0.9649 |
135 | 0.03069 | 0.06139 | 0.9693 |
136 | 0.02872 | 0.05743 | 0.9713 |
137 | 0.02677 | 0.05354 | 0.9732 |
138 | 0.03167 | 0.06335 | 0.9683 |
139 | 0.02394 | 0.04788 | 0.9761 |
140 | 0.01729 | 0.03457 | 0.9827 |
141 | 0.03151 | 0.06303 | 0.9685 |
142 | 0.03082 | 0.06165 | 0.9692 |
143 | 0.03014 | 0.06028 | 0.9699 |
144 | 0.1129 | 0.2257 | 0.8871 |
145 | 0.105 | 0.21 | 0.895 |
146 | 0.07923 | 0.1585 | 0.9208 |
147 | 0.09124 | 0.1825 | 0.9088 |
148 | 0.07733 | 0.1547 | 0.9227 |
149 | 0.0836 | 0.1672 | 0.9164 |
150 | 0.05734 | 0.1147 | 0.9427 |
151 | 0.06084 | 0.1217 | 0.9392 |
152 | 0.04003 | 0.08007 | 0.96 |
153 | 0.03527 | 0.07054 | 0.9647 |
154 | 0.07002 | 0.14 | 0.93 |
155 | 0.04465 | 0.08931 | 0.9553 |
156 | 0.08392 | 0.1678 | 0.9161 |
157 | 0.04548 | 0.09097 | 0.9545 |
158 | 0.1408 | 0.2816 | 0.8592 |
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | |||
Description | # significant tests | % significant tests | OK/NOK |
1% type I error level | 31 | 0.2039 | NOK |
5% type I error level | 67 | 0.440789 | NOK |
10% type I error level | 96 | 0.631579 | NOK |
Ramsey RESET F-Test for powers (2 and 3) of fitted values |
> reset_test_fitted RESET test data: mylm RESET = 1.6335, df1 = 2, df2 = 159, p-value = 0.1985 |
Ramsey RESET F-Test for powers (2 and 3) of regressors |
> reset_test_regressors RESET test data: mylm RESET = 1.877, df1 = 6, df2 = 155, p-value = 0.08805 |
Ramsey RESET F-Test for powers (2 and 3) of principal components |
> reset_test_principal_components RESET test data: mylm RESET = 0.30827, df1 = 2, df2 = 159, p-value = 0.7352 |
Variance Inflation Factors (Multicollinearity) |
> vif SK1 SK2 SK4 1.090360 1.099743 1.050502 |