Multiple Linear Regression - Estimated Regression Equation |
TVDCSUM[t] = + 12.7553 + 0.0985915EP1[t] -0.2217EP2[t] -0.277576EP3[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) | +12.76 | 0.5835 | +2.1860e+01 | 1.838e-50 | 9.19e-51 |
EP1 | +0.09859 | 0.1647 | +5.9870e-01 | 0.5502 | 0.2751 |
EP2 | -0.2217 | 0.1557 | -1.4240e+00 | 0.1562 | 0.07812 |
EP3 | -0.2776 | 0.09471 | -2.9310e+00 | 0.003865 | 0.001932 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.2578 |
R-squared | 0.06644 |
Adjusted R-squared | 0.04936 |
F-TEST (value) | 3.891 |
F-TEST (DF numerator) | 3 |
F-TEST (DF denominator) | 164 |
p-value | 0.01017 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 1.193 |
Sum Squared Residuals | 233.3 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 9 | 11.03 | -2.029 |
2 | 11 | 11.83 | -0.8308 |
3 | 13 | 11.31 | 1.693 |
4 | 11 | 11.81 | -0.8063 |
5 | 12 | 11.81 | 0.1937 |
6 | 11 | 11.31 | -0.307 |
7 | 12 | 11.75 | 0.2496 |
8 | 12 | 11.58 | 0.4154 |
9 | 13 | 11.58 | 1.415 |
10 | 12 | 11.03 | 0.9706 |
11 | 12 | 11.49 | 0.514 |
12 | 11 | 11.51 | -0.5105 |
13 | 12 | 11.53 | 0.4713 |
14 | 10 | 11.49 | -1.486 |
15 | 12 | 11.31 | 0.693 |
16 | 12 | 11.49 | 0.514 |
17 | 12 | 11.81 | 0.1937 |
18 | 12 | 10.75 | 1.248 |
19 | 13 | 11.31 | 1.693 |
20 | 11 | 11.49 | -0.486 |
21 | 11 | 11.49 | -0.486 |
22 | 11 | 11.33 | -0.3315 |
23 | 11 | 11.86 | -0.8622 |
24 | 13 | 11.71 | 1.292 |
25 | 11 | 11.31 | -0.307 |
26 | 12 | 11.71 | 0.2923 |
27 | 11 | 11.58 | -0.5846 |
28 | 12 | 11.53 | 0.4713 |
29 | 12 | 10.75 | 1.248 |
30 | 10 | 11.58 | -1.585 |
31 | 11 | 10.75 | 0.2481 |
32 | 12 | 11.58 | 0.4154 |
33 | 11 | 11.58 | -0.5846 |
34 | 9 | 11.25 | -2.251 |
35 | 12 | 12.08 | -0.08387 |
36 | 11 | 11.71 | -0.7077 |
37 | 11 | 11.71 | -0.7077 |
38 | 12 | 11.31 | 0.693 |
39 | 13 | 11.58 | 1.415 |
40 | 11 | 11.31 | -0.307 |
41 | 12 | 11.58 | 0.4154 |
42 | 9 | 11.31 | -2.307 |
43 | 12 | 11.03 | 0.9706 |
44 | 11 | 11.03 | -0.02944 |
45 | 12 | 11.31 | 0.693 |
46 | 12 | 11.58 | 0.4154 |
47 | 11 | 11.81 | -0.8063 |
48 | 10 | 10.93 | -0.9308 |
49 | 9 | 11.03 | -2.029 |
50 | 12 | 11.31 | 0.693 |
51 | 13 | 11.71 | 1.292 |
52 | 13 | 11.58 | 1.415 |
53 | 9 | 11.61 | -2.609 |
54 | 11 | 11.93 | -0.9294 |
55 | 11 | 11.55 | -0.5532 |
56 | 11 | 11.81 | -0.8063 |
57 | 12 | 11.58 | 0.4154 |
58 | 12 | 11.31 | 0.693 |
59 | 11 | 11.53 | -0.5287 |
60 | 12 | 11.58 | 0.4154 |
61 | 11 | 11.58 | -0.5846 |
62 | 12 | 11.03 | 0.9706 |
63 | 11 | 11.03 | -0.02944 |
64 | 11 | 11.43 | -0.4301 |
65 | 8 | 11.03 | -3.029 |
66 | 12 | 11.15 | 0.8475 |
67 | 11 | 11.03 | -0.02944 |
68 | 12 | 11.4 | 0.6012 |
69 | 11 | 11.1 | -0.09667 |
70 | 11 | 11.31 | -0.307 |
71 | 11 | 11.03 | -0.02944 |
72 | 10 | 11.37 | -1.374 |
73 | 10 | 11.58 | -1.585 |
74 | 13 | 11.73 | 1.268 |
75 | 11 | 11.53 | -0.5287 |
76 | 11 | 11.28 | -0.2757 |
77 | 11 | 11.49 | -0.486 |
78 | 13 | 10.88 | 2.125 |
79 | 12 | 11.86 | 0.1378 |
80 | 12 | 11.31 | 0.693 |
81 | 9 | 11.43 | -2.43 |
82 | 12 | 11.71 | 0.2923 |
83 | 12 | 11.58 | 0.4154 |
84 | 13 | 11.76 | 1.236 |
85 | 15 | 11.71 | 3.292 |
86 | 13 | 11.86 | 1.138 |
87 | 13 | 11.58 | 1.415 |
88 | 11 | 11.58 | -0.5846 |
89 | 12 | 11.71 | 0.2923 |
90 | 9 | 11.71 | -2.708 |
91 | 11 | 11.43 | -0.4301 |
92 | 13 | 11.83 | 1.169 |
93 | 12 | 11.99 | 0.01472 |
94 | 13 | 11.86 | 1.138 |
95 | 11 | 11.31 | -0.307 |
96 | 12 | 11.71 | 0.2923 |
97 | 14 | 11.31 | 2.693 |
98 | 13 | 12.23 | 0.7685 |
99 | 11 | 11.58 | -0.5846 |
100 | 12 | 11.58 | 0.4154 |
101 | 13 | 11.43 | 1.57 |
102 | 11 | 11.39 | -0.3874 |
103 | 11 | 11.58 | -0.5846 |
104 | 11 | 11.43 | -0.4301 |
105 | 13 | 11.86 | 1.138 |
106 | 12 | 11.03 | 0.9706 |
107 | 12 | 11.31 | 0.693 |
108 | 11 | 11.58 | -0.5846 |
109 | 12 | 11.31 | 0.693 |
110 | 12 | 11.21 | 0.7916 |
111 | 10 | 11.53 | -1.529 |
112 | 11 | 11.03 | -0.02944 |
113 | 9 | 11.75 | -2.75 |
114 | 14 | 11.71 | 2.292 |
115 | 12 | 11.31 | 0.693 |
116 | 11 | 11.58 | -0.5846 |
117 | 13 | 12.45 | 0.5468 |
118 | 11 | 11.86 | -0.8622 |
119 | 11 | 11.58 | -0.5846 |
120 | 11 | 11.25 | -0.2511 |
121 | 11 | 11.53 | -0.5287 |
122 | 12 | 11.58 | 0.4154 |
123 | 11 | 11.58 | -0.5846 |
124 | 13 | 11.31 | 1.693 |
125 | 11 | 11.31 | -0.307 |
126 | 11 | 11.21 | -0.2084 |
127 | 12 | 11.83 | 0.1692 |
128 | 11 | 11.81 | -0.8063 |
129 | 11 | 11.58 | -0.5846 |
130 | 9 | 11.31 | -2.307 |
131 | 12 | 11.03 | 0.9706 |
132 | 14 | 11.71 | 2.292 |
133 | 10 | 11.49 | -1.486 |
134 | 9 | 11.99 | -2.985 |
135 | 12 | 11.53 | 0.4713 |
136 | 14 | 11.43 | 2.57 |
137 | 9 | 11.05 | -2.054 |
138 | 11 | 11.43 | -0.4301 |
139 | 14 | 11.86 | 2.138 |
140 | 13 | 12.23 | 0.7685 |
141 | 10 | 11.58 | -1.585 |
142 | 11 | 11.99 | -0.9853 |
143 | 12 | 10.75 | 1.248 |
144 | 10 | 11.31 | -1.307 |
145 | 13 | 11.71 | 1.292 |
146 | 12 | 11.81 | 0.1937 |
147 | 14 | 11.6 | 2.404 |
148 | 10 | 11.58 | -1.585 |
149 | 12 | 11.03 | 0.9706 |
150 | 9 | 11.03 | -2.029 |
151 | 12 | 11.43 | 0.5699 |
152 | 11 | 11.03 | -0.02944 |
153 | 11 | 11.31 | -0.307 |
154 | 10 | 11.25 | -1.251 |
155 | 11 | 11.31 | -0.307 |
156 | 12 | 11.03 | 0.9706 |
157 | 10 | 11.95 | -1.954 |
158 | 11 | 11.03 | -0.02944 |
159 | 13 | 12.11 | 0.8916 |
160 | 11 | 11.03 | -0.02944 |
161 | 13 | 11.53 | 1.471 |
162 | 12 | 11.58 | 0.4154 |
163 | 11 | 11.71 | -0.7077 |
164 | 12 | 11.58 | 0.4154 |
165 | 10 | 11.03 | -1.029 |
166 | 12 | 11.31 | 0.693 |
167 | 10 | 11.53 | -1.529 |
168 | 13 | 12.25 | 0.7503 |
Goldfeld-Quandt test for Heteroskedasticity | |||
p-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
7 | 0.8022 | 0.3957 | 0.1978 |
8 | 0.6756 | 0.6487 | 0.3244 |
9 | 0.6052 | 0.7897 | 0.3948 |
10 | 0.638 | 0.7241 | 0.362 |
11 | 0.5274 | 0.9452 | 0.4726 |
12 | 0.4184 | 0.8369 | 0.5816 |
13 | 0.3382 | 0.6765 | 0.6618 |
14 | 0.4364 | 0.8728 | 0.5636 |
15 | 0.3618 | 0.7235 | 0.6382 |
16 | 0.2908 | 0.5817 | 0.7092 |
17 | 0.2202 | 0.4404 | 0.7798 |
18 | 0.2185 | 0.4369 | 0.7815 |
19 | 0.2361 | 0.4722 | 0.7639 |
20 | 0.1928 | 0.3857 | 0.8072 |
21 | 0.1531 | 0.3062 | 0.8469 |
22 | 0.1131 | 0.2262 | 0.8869 |
23 | 0.106 | 0.2121 | 0.894 |
24 | 0.1347 | 0.2694 | 0.8653 |
25 | 0.1116 | 0.2233 | 0.8884 |
26 | 0.08516 | 0.1703 | 0.9148 |
27 | 0.07151 | 0.143 | 0.9285 |
28 | 0.05171 | 0.1034 | 0.9483 |
29 | 0.04057 | 0.08115 | 0.9594 |
30 | 0.06276 | 0.1255 | 0.9372 |
31 | 0.04945 | 0.09891 | 0.9505 |
32 | 0.03696 | 0.07393 | 0.963 |
33 | 0.02889 | 0.05778 | 0.9711 |
34 | 0.113 | 0.2259 | 0.887 |
35 | 0.08718 | 0.1744 | 0.9128 |
36 | 0.07022 | 0.1404 | 0.9298 |
37 | 0.05582 | 0.1116 | 0.9442 |
38 | 0.04445 | 0.08889 | 0.9556 |
39 | 0.05118 | 0.1024 | 0.9488 |
40 | 0.04042 | 0.08084 | 0.9596 |
41 | 0.03041 | 0.06081 | 0.9696 |
42 | 0.08885 | 0.1777 | 0.9111 |
43 | 0.07779 | 0.1556 | 0.9222 |
44 | 0.06088 | 0.1218 | 0.9391 |
45 | 0.04975 | 0.0995 | 0.9503 |
46 | 0.0386 | 0.07721 | 0.9614 |
47 | 0.03247 | 0.06494 | 0.9675 |
48 | 0.0305 | 0.06099 | 0.9695 |
49 | 0.06238 | 0.1248 | 0.9376 |
50 | 0.05215 | 0.1043 | 0.9478 |
51 | 0.0617 | 0.1234 | 0.9383 |
52 | 0.06725 | 0.1345 | 0.9327 |
53 | 0.1275 | 0.255 | 0.8725 |
54 | 0.1095 | 0.2191 | 0.8905 |
55 | 0.09123 | 0.1825 | 0.9088 |
56 | 0.08041 | 0.1608 | 0.9196 |
57 | 0.06487 | 0.1297 | 0.9351 |
58 | 0.05435 | 0.1087 | 0.9456 |
59 | 0.04404 | 0.08808 | 0.956 |
60 | 0.03457 | 0.06915 | 0.9654 |
61 | 0.02915 | 0.05831 | 0.9708 |
62 | 0.02599 | 0.05198 | 0.974 |
63 | 0.01971 | 0.03942 | 0.9803 |
64 | 0.01491 | 0.02982 | 0.9851 |
65 | 0.07614 | 0.1523 | 0.9239 |
66 | 0.07481 | 0.1496 | 0.9252 |
67 | 0.0597 | 0.1194 | 0.9403 |
68 | 0.06169 | 0.1234 | 0.9383 |
69 | 0.04887 | 0.09773 | 0.9511 |
70 | 0.03898 | 0.07796 | 0.961 |
71 | 0.0302 | 0.06041 | 0.9698 |
72 | 0.0313 | 0.06259 | 0.9687 |
73 | 0.03864 | 0.07728 | 0.9614 |
74 | 0.04639 | 0.09278 | 0.9536 |
75 | 0.03782 | 0.07564 | 0.9622 |
76 | 0.02979 | 0.05958 | 0.9702 |
77 | 0.02385 | 0.0477 | 0.9762 |
78 | 0.04188 | 0.08375 | 0.9581 |
79 | 0.03306 | 0.06613 | 0.9669 |
80 | 0.02789 | 0.05577 | 0.9721 |
81 | 0.05842 | 0.1168 | 0.9416 |
82 | 0.04773 | 0.09545 | 0.9523 |
83 | 0.03882 | 0.07764 | 0.9612 |
84 | 0.04029 | 0.08057 | 0.9597 |
85 | 0.1617 | 0.3235 | 0.8383 |
86 | 0.1595 | 0.319 | 0.8405 |
87 | 0.1704 | 0.3407 | 0.8296 |
88 | 0.1495 | 0.2989 | 0.8505 |
89 | 0.1264 | 0.2529 | 0.8736 |
90 | 0.2416 | 0.4832 | 0.7584 |
91 | 0.2123 | 0.4245 | 0.7877 |
92 | 0.2124 | 0.4249 | 0.7876 |
93 | 0.1813 | 0.3626 | 0.8187 |
94 | 0.18 | 0.3601 | 0.8199 |
95 | 0.1537 | 0.3075 | 0.8463 |
96 | 0.13 | 0.2601 | 0.87 |
97 | 0.2483 | 0.4965 | 0.7517 |
98 | 0.2284 | 0.4568 | 0.7716 |
99 | 0.2021 | 0.4042 | 0.7979 |
100 | 0.1761 | 0.3522 | 0.8239 |
101 | 0.1959 | 0.3919 | 0.8041 |
102 | 0.1687 | 0.3373 | 0.8313 |
103 | 0.1466 | 0.2932 | 0.8534 |
104 | 0.1248 | 0.2495 | 0.8752 |
105 | 0.1265 | 0.2531 | 0.8735 |
106 | 0.1176 | 0.2352 | 0.8824 |
107 | 0.1039 | 0.2078 | 0.8961 |
108 | 0.08774 | 0.1755 | 0.9123 |
109 | 0.07682 | 0.1536 | 0.9232 |
110 | 0.06847 | 0.1369 | 0.9315 |
111 | 0.07691 | 0.1538 | 0.9231 |
112 | 0.06136 | 0.1227 | 0.9386 |
113 | 0.1633 | 0.3266 | 0.8367 |
114 | 0.2641 | 0.5282 | 0.7359 |
115 | 0.2427 | 0.4855 | 0.7573 |
116 | 0.2116 | 0.4231 | 0.7884 |
117 | 0.1847 | 0.3693 | 0.8153 |
118 | 0.1631 | 0.3261 | 0.8369 |
119 | 0.1384 | 0.2768 | 0.8616 |
120 | 0.1173 | 0.2345 | 0.8827 |
121 | 0.1021 | 0.2043 | 0.8979 |
122 | 0.08632 | 0.1726 | 0.9137 |
123 | 0.07041 | 0.1408 | 0.9296 |
124 | 0.09232 | 0.1846 | 0.9077 |
125 | 0.07356 | 0.1471 | 0.9264 |
126 | 0.0592 | 0.1184 | 0.9408 |
127 | 0.04604 | 0.09207 | 0.954 |
128 | 0.04083 | 0.08166 | 0.9592 |
129 | 0.03171 | 0.06341 | 0.9683 |
130 | 0.057 | 0.114 | 0.943 |
131 | 0.05193 | 0.1039 | 0.9481 |
132 | 0.108 | 0.2161 | 0.892 |
133 | 0.1001 | 0.2002 | 0.8999 |
134 | 0.2467 | 0.4935 | 0.7533 |
135 | 0.2064 | 0.4129 | 0.7936 |
136 | 0.3991 | 0.7981 | 0.6009 |
137 | 0.4356 | 0.8712 | 0.5644 |
138 | 0.3822 | 0.7643 | 0.6178 |
139 | 0.5824 | 0.8353 | 0.4177 |
140 | 0.5533 | 0.8934 | 0.4467 |
141 | 0.5574 | 0.8852 | 0.4426 |
142 | 0.5117 | 0.9767 | 0.4883 |
143 | 0.5248 | 0.9505 | 0.4752 |
144 | 0.5197 | 0.9607 | 0.4803 |
145 | 0.5574 | 0.8851 | 0.4426 |
146 | 0.4869 | 0.9738 | 0.5131 |
147 | 0.676 | 0.6479 | 0.324 |
148 | 0.7993 | 0.4014 | 0.2007 |
149 | 0.8259 | 0.3483 | 0.1741 |
150 | 0.8906 | 0.2187 | 0.1094 |
151 | 0.8889 | 0.2223 | 0.1111 |
152 | 0.8449 | 0.3101 | 0.1551 |
153 | 0.7938 | 0.4125 | 0.2062 |
154 | 0.7696 | 0.4608 | 0.2304 |
155 | 0.705 | 0.5899 | 0.295 |
156 | 0.7355 | 0.529 | 0.2645 |
157 | 0.7094 | 0.5812 | 0.2906 |
158 | 0.6097 | 0.7805 | 0.3903 |
159 | 0.5839 | 0.8323 | 0.4161 |
160 | 0.4636 | 0.9271 | 0.5364 |
161 | 0.6261 | 0.7478 | 0.3739 |
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 | 3 | 0.0193548 | OK |
10% type I error level | 35 | 0.225806 | NOK |
Ramsey RESET F-Test for powers (2 and 3) of fitted values |
> reset_test_fitted RESET test data: mylm RESET = 1.1591, df1 = 2, df2 = 162, p-value = 0.3164 |
Ramsey RESET F-Test for powers (2 and 3) of regressors |
> reset_test_regressors RESET test data: mylm RESET = 1.2486, df1 = 6, df2 = 158, p-value = 0.2845 |
Ramsey RESET F-Test for powers (2 and 3) of principal components |
> reset_test_principal_components RESET test data: mylm RESET = 0.78168, df1 = 2, df2 = 162, p-value = 0.4594 |
Variance Inflation Factors (Multicollinearity) |
> vif EP1 EP2 EP3 1.981945 1.924055 1.046453 |