Multiple Linear Regression - Estimated Regression Equation |
TVDCSUM[t] = + 12.2345 -0.283388EP3[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) | +12.23 | 0.2627 | +4.6570e+01 | 3.226e-97 | 1.613e-97 |
EP3 | -0.2834 | 0.09267 | -3.0580e+00 | 0.002598 | 0.001299 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.2309 |
R-squared | 0.05333 |
Adjusted R-squared | 0.04763 |
F-TEST (value) | 9.351 |
F-TEST (DF numerator) | 1 |
F-TEST (DF denominator) | 166 |
p-value | 0.002598 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 1.194 |
Sum Squared Residuals | 236.6 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 9 | 11.1 | -2.101 |
2 | 11 | 11.67 | -0.6677 |
3 | 13 | 11.38 | 1.616 |
4 | 11 | 11.67 | -0.6677 |
5 | 12 | 11.67 | 0.3323 |
6 | 11 | 11.38 | -0.3843 |
7 | 12 | 11.38 | 0.6157 |
8 | 12 | 11.67 | 0.3323 |
9 | 13 | 11.67 | 1.332 |
10 | 12 | 11.1 | 0.8991 |
11 | 12 | 11.67 | 0.3323 |
12 | 11 | 11.67 | -0.6677 |
13 | 12 | 11.38 | 0.6157 |
14 | 10 | 11.67 | -1.668 |
15 | 12 | 11.38 | 0.6157 |
16 | 12 | 11.67 | 0.3323 |
17 | 12 | 11.67 | 0.3323 |
18 | 12 | 10.82 | 1.182 |
19 | 13 | 11.38 | 1.616 |
20 | 11 | 11.67 | -0.6677 |
21 | 11 | 11.67 | -0.6677 |
22 | 11 | 11.38 | -0.3843 |
23 | 11 | 11.95 | -0.9511 |
24 | 13 | 11.67 | 1.332 |
25 | 11 | 11.38 | -0.3843 |
26 | 12 | 11.67 | 0.3323 |
27 | 11 | 11.67 | -0.6677 |
28 | 12 | 11.38 | 0.6157 |
29 | 12 | 10.82 | 1.182 |
30 | 10 | 11.67 | -1.668 |
31 | 11 | 10.82 | 0.1825 |
32 | 12 | 11.67 | 0.3323 |
33 | 11 | 11.67 | -0.6677 |
34 | 9 | 11.1 | -2.101 |
35 | 12 | 11.95 | 0.04892 |
36 | 11 | 11.67 | -0.6677 |
37 | 11 | 11.67 | -0.6677 |
38 | 12 | 11.38 | 0.6157 |
39 | 13 | 11.67 | 1.332 |
40 | 11 | 11.38 | -0.3843 |
41 | 12 | 11.67 | 0.3323 |
42 | 9 | 11.38 | -2.384 |
43 | 12 | 11.1 | 0.8991 |
44 | 11 | 11.1 | -0.1009 |
45 | 12 | 11.38 | 0.6157 |
46 | 12 | 11.67 | 0.3323 |
47 | 11 | 11.67 | -0.6677 |
48 | 10 | 11.1 | -1.101 |
49 | 9 | 11.1 | -2.101 |
50 | 12 | 11.38 | 0.6157 |
51 | 13 | 11.67 | 1.332 |
52 | 13 | 11.67 | 1.332 |
53 | 9 | 11.67 | -2.668 |
54 | 11 | 11.67 | -0.6677 |
55 | 11 | 11.38 | -0.3843 |
56 | 11 | 11.67 | -0.6677 |
57 | 12 | 11.67 | 0.3323 |
58 | 12 | 11.38 | 0.6157 |
59 | 11 | 11.38 | -0.3843 |
60 | 12 | 11.67 | 0.3323 |
61 | 11 | 11.67 | -0.6677 |
62 | 12 | 11.1 | 0.8991 |
63 | 11 | 11.1 | -0.1009 |
64 | 11 | 11.38 | -0.3843 |
65 | 8 | 11.1 | -3.101 |
66 | 12 | 11.1 | 0.8991 |
67 | 11 | 11.1 | -0.1009 |
68 | 12 | 11.1 | 0.8991 |
69 | 11 | 10.82 | 0.1825 |
70 | 11 | 11.38 | -0.3843 |
71 | 11 | 11.1 | -0.1009 |
72 | 10 | 11.1 | -1.101 |
73 | 10 | 11.67 | -1.668 |
74 | 13 | 11.67 | 1.332 |
75 | 11 | 11.38 | -0.3843 |
76 | 11 | 11.1 | -0.1009 |
77 | 11 | 11.67 | -0.6677 |
78 | 13 | 10.82 | 2.182 |
79 | 12 | 11.95 | 0.04892 |
80 | 12 | 11.38 | 0.6157 |
81 | 9 | 11.38 | -2.384 |
82 | 12 | 11.67 | 0.3323 |
83 | 12 | 11.67 | 0.3323 |
84 | 13 | 11.95 | 1.049 |
85 | 15 | 11.67 | 3.332 |
86 | 13 | 11.95 | 1.049 |
87 | 13 | 11.67 | 1.332 |
88 | 11 | 11.67 | -0.6677 |
89 | 12 | 11.67 | 0.3323 |
90 | 9 | 11.67 | -2.668 |
91 | 11 | 11.38 | -0.3843 |
92 | 13 | 11.67 | 1.332 |
93 | 12 | 11.95 | 0.04892 |
94 | 13 | 11.95 | 1.049 |
95 | 11 | 11.38 | -0.3843 |
96 | 12 | 11.67 | 0.3323 |
97 | 14 | 11.38 | 2.616 |
98 | 13 | 11.95 | 1.049 |
99 | 11 | 11.67 | -0.6677 |
100 | 12 | 11.67 | 0.3323 |
101 | 13 | 11.38 | 1.616 |
102 | 11 | 11.67 | -0.6677 |
103 | 11 | 11.67 | -0.6677 |
104 | 11 | 11.38 | -0.3843 |
105 | 13 | 11.95 | 1.049 |
106 | 12 | 11.1 | 0.8991 |
107 | 12 | 11.38 | 0.6157 |
108 | 11 | 11.67 | -0.6677 |
109 | 12 | 11.38 | 0.6157 |
110 | 12 | 11.38 | 0.6157 |
111 | 10 | 11.38 | -1.384 |
112 | 11 | 11.1 | -0.1009 |
113 | 9 | 11.38 | -2.384 |
114 | 14 | 11.67 | 2.332 |
115 | 12 | 11.38 | 0.6157 |
116 | 11 | 11.67 | -0.6677 |
117 | 13 | 11.95 | 1.049 |
118 | 11 | 11.95 | -0.9511 |
119 | 11 | 11.67 | -0.6677 |
120 | 11 | 11.1 | -0.1009 |
121 | 11 | 11.38 | -0.3843 |
122 | 12 | 11.67 | 0.3323 |
123 | 11 | 11.67 | -0.6677 |
124 | 13 | 11.38 | 1.616 |
125 | 11 | 11.38 | -0.3843 |
126 | 11 | 11.38 | -0.3843 |
127 | 12 | 11.67 | 0.3323 |
128 | 11 | 11.67 | -0.6677 |
129 | 11 | 11.67 | -0.6677 |
130 | 9 | 11.38 | -2.384 |
131 | 12 | 11.1 | 0.8991 |
132 | 14 | 11.67 | 2.332 |
133 | 10 | 11.67 | -1.668 |
134 | 9 | 11.95 | -2.951 |
135 | 12 | 11.38 | 0.6157 |
136 | 14 | 11.38 | 2.616 |
137 | 9 | 11.1 | -2.101 |
138 | 11 | 11.38 | -0.3843 |
139 | 14 | 11.95 | 2.049 |
140 | 13 | 11.95 | 1.049 |
141 | 10 | 11.67 | -1.668 |
142 | 11 | 11.95 | -0.9511 |
143 | 12 | 10.82 | 1.182 |
144 | 10 | 11.38 | -1.384 |
145 | 13 | 11.67 | 1.332 |
146 | 12 | 11.67 | 0.3323 |
147 | 14 | 11.1 | 2.899 |
148 | 10 | 11.67 | -1.668 |
149 | 12 | 11.1 | 0.8991 |
150 | 9 | 11.1 | -2.101 |
151 | 12 | 11.38 | 0.6157 |
152 | 11 | 11.1 | -0.1009 |
153 | 11 | 11.38 | -0.3843 |
154 | 10 | 11.1 | -1.101 |
155 | 11 | 11.38 | -0.3843 |
156 | 12 | 11.1 | 0.8991 |
157 | 10 | 11.67 | -1.668 |
158 | 11 | 11.1 | -0.1009 |
159 | 13 | 11.95 | 1.049 |
160 | 11 | 11.1 | -0.1009 |
161 | 13 | 11.38 | 1.616 |
162 | 12 | 11.67 | 0.3323 |
163 | 11 | 11.67 | -0.6677 |
164 | 12 | 11.67 | 0.3323 |
165 | 10 | 11.1 | -1.101 |
166 | 12 | 11.38 | 0.6157 |
167 | 10 | 11.38 | -1.384 |
168 | 13 | 11.67 | 1.332 |
Goldfeld-Quandt test for Heteroskedasticity | |||
p-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
5 | 0.8013 | 0.3973 | 0.1987 |
6 | 0.6754 | 0.6492 | 0.3246 |
7 | 0.6237 | 0.7527 | 0.3763 |
8 | 0.4995 | 0.999 | 0.5005 |
9 | 0.4738 | 0.9477 | 0.5262 |
10 | 0.5047 | 0.9906 | 0.4953 |
11 | 0.4013 | 0.8027 | 0.5987 |
12 | 0.3623 | 0.7245 | 0.6377 |
13 | 0.297 | 0.5941 | 0.703 |
14 | 0.406 | 0.8121 | 0.594 |
15 | 0.3443 | 0.6886 | 0.6557 |
16 | 0.2749 | 0.5499 | 0.7251 |
17 | 0.214 | 0.4281 | 0.786 |
18 | 0.1901 | 0.3802 | 0.8099 |
19 | 0.2209 | 0.4418 | 0.7791 |
20 | 0.1877 | 0.3753 | 0.8123 |
21 | 0.1562 | 0.3124 | 0.8438 |
22 | 0.1268 | 0.2535 | 0.8732 |
23 | 0.1027 | 0.2055 | 0.8973 |
24 | 0.1239 | 0.2478 | 0.8761 |
25 | 0.1005 | 0.201 | 0.8995 |
26 | 0.07664 | 0.1533 | 0.9234 |
27 | 0.06177 | 0.1235 | 0.9382 |
28 | 0.04668 | 0.09336 | 0.9533 |
29 | 0.03585 | 0.07169 | 0.9642 |
30 | 0.0527 | 0.1054 | 0.9473 |
31 | 0.0425 | 0.08499 | 0.9575 |
32 | 0.03206 | 0.06411 | 0.9679 |
33 | 0.0249 | 0.0498 | 0.9751 |
34 | 0.08282 | 0.1656 | 0.9172 |
35 | 0.06439 | 0.1288 | 0.9356 |
36 | 0.05195 | 0.1039 | 0.948 |
37 | 0.04145 | 0.08289 | 0.9586 |
38 | 0.03306 | 0.06612 | 0.9669 |
39 | 0.0408 | 0.08159 | 0.9592 |
40 | 0.03162 | 0.06323 | 0.9684 |
41 | 0.02406 | 0.04812 | 0.9759 |
42 | 0.0705 | 0.141 | 0.9295 |
43 | 0.0612 | 0.1224 | 0.9388 |
44 | 0.04746 | 0.09492 | 0.9525 |
45 | 0.03873 | 0.07745 | 0.9613 |
46 | 0.03018 | 0.06036 | 0.9698 |
47 | 0.02426 | 0.04851 | 0.9757 |
48 | 0.02585 | 0.0517 | 0.9741 |
49 | 0.05356 | 0.1071 | 0.9464 |
50 | 0.04496 | 0.08993 | 0.955 |
51 | 0.05135 | 0.1027 | 0.9487 |
52 | 0.05724 | 0.1145 | 0.9428 |
53 | 0.1421 | 0.2842 | 0.8579 |
54 | 0.1229 | 0.2457 | 0.8771 |
55 | 0.1019 | 0.2037 | 0.8981 |
56 | 0.0868 | 0.1736 | 0.9132 |
57 | 0.07146 | 0.1429 | 0.9285 |
58 | 0.06088 | 0.1218 | 0.9391 |
59 | 0.04891 | 0.09781 | 0.9511 |
60 | 0.03925 | 0.07849 | 0.9608 |
61 | 0.03246 | 0.06493 | 0.9675 |
62 | 0.02897 | 0.05794 | 0.971 |
63 | 0.0221 | 0.0442 | 0.9779 |
64 | 0.01709 | 0.03419 | 0.9829 |
65 | 0.0802 | 0.1604 | 0.9198 |
66 | 0.07413 | 0.1483 | 0.9259 |
67 | 0.05934 | 0.1187 | 0.9407 |
68 | 0.05421 | 0.1084 | 0.9458 |
69 | 0.04289 | 0.08578 | 0.9571 |
70 | 0.03423 | 0.06846 | 0.9658 |
71 | 0.02647 | 0.05294 | 0.9735 |
72 | 0.02565 | 0.05129 | 0.9744 |
73 | 0.03225 | 0.0645 | 0.9678 |
74 | 0.03609 | 0.07218 | 0.9639 |
75 | 0.02868 | 0.05737 | 0.9713 |
76 | 0.02209 | 0.04418 | 0.9779 |
77 | 0.01814 | 0.03628 | 0.9819 |
78 | 0.03366 | 0.06732 | 0.9663 |
79 | 0.02645 | 0.0529 | 0.9736 |
80 | 0.02199 | 0.04399 | 0.978 |
81 | 0.04673 | 0.09346 | 0.9533 |
82 | 0.03794 | 0.07588 | 0.9621 |
83 | 0.03052 | 0.06105 | 0.9695 |
84 | 0.02986 | 0.05972 | 0.9701 |
85 | 0.1325 | 0.265 | 0.8675 |
86 | 0.1274 | 0.2548 | 0.8726 |
87 | 0.1329 | 0.2658 | 0.8671 |
88 | 0.1171 | 0.2341 | 0.8829 |
89 | 0.09812 | 0.1962 | 0.9019 |
90 | 0.1952 | 0.3904 | 0.8048 |
91 | 0.1689 | 0.3379 | 0.8311 |
92 | 0.1751 | 0.3502 | 0.8249 |
93 | 0.148 | 0.296 | 0.852 |
94 | 0.1417 | 0.2835 | 0.8583 |
95 | 0.1205 | 0.241 | 0.8795 |
96 | 0.101 | 0.2021 | 0.899 |
97 | 0.1929 | 0.3858 | 0.8071 |
98 | 0.1859 | 0.3718 | 0.8141 |
99 | 0.1655 | 0.331 | 0.8345 |
100 | 0.1411 | 0.2822 | 0.8589 |
101 | 0.1617 | 0.3234 | 0.8383 |
102 | 0.1428 | 0.2857 | 0.8572 |
103 | 0.1255 | 0.2511 | 0.8745 |
104 | 0.1056 | 0.2113 | 0.8944 |
105 | 0.1012 | 0.2023 | 0.8988 |
106 | 0.09218 | 0.1844 | 0.9078 |
107 | 0.07912 | 0.1582 | 0.9209 |
108 | 0.06765 | 0.1353 | 0.9323 |
109 | 0.05735 | 0.1147 | 0.9427 |
110 | 0.04834 | 0.09669 | 0.9517 |
111 | 0.05109 | 0.1022 | 0.9489 |
112 | 0.04011 | 0.08022 | 0.9599 |
113 | 0.0759 | 0.1518 | 0.9241 |
114 | 0.1316 | 0.2631 | 0.8684 |
115 | 0.114 | 0.228 | 0.886 |
116 | 0.09799 | 0.196 | 0.902 |
117 | 0.09512 | 0.1902 | 0.9049 |
118 | 0.0852 | 0.1704 | 0.9148 |
119 | 0.07206 | 0.1441 | 0.9279 |
120 | 0.05705 | 0.1141 | 0.9429 |
121 | 0.0455 | 0.091 | 0.9545 |
122 | 0.03592 | 0.07183 | 0.9641 |
123 | 0.02926 | 0.05851 | 0.9707 |
124 | 0.03546 | 0.07092 | 0.9645 |
125 | 0.02745 | 0.05491 | 0.9725 |
126 | 0.02099 | 0.04198 | 0.979 |
127 | 0.01591 | 0.03183 | 0.9841 |
128 | 0.01246 | 0.02492 | 0.9875 |
129 | 0.009678 | 0.01936 | 0.9903 |
130 | 0.02174 | 0.04348 | 0.9783 |
131 | 0.01834 | 0.03667 | 0.9817 |
132 | 0.03852 | 0.07703 | 0.9615 |
133 | 0.04579 | 0.09157 | 0.9542 |
134 | 0.1446 | 0.2893 | 0.8554 |
135 | 0.1214 | 0.2428 | 0.8786 |
136 | 0.2428 | 0.4856 | 0.7572 |
137 | 0.3267 | 0.6534 | 0.6733 |
138 | 0.2818 | 0.5636 | 0.7182 |
139 | 0.3748 | 0.7497 | 0.6252 |
140 | 0.3751 | 0.7503 | 0.6249 |
141 | 0.413 | 0.8259 | 0.587 |
142 | 0.3841 | 0.7681 | 0.6159 |
143 | 0.3816 | 0.7633 | 0.6184 |
144 | 0.4018 | 0.8035 | 0.5982 |
145 | 0.4061 | 0.8122 | 0.5939 |
146 | 0.347 | 0.6939 | 0.653 |
147 | 0.7086 | 0.5828 | 0.2914 |
148 | 0.7896 | 0.4208 | 0.2104 |
149 | 0.8035 | 0.393 | 0.1965 |
150 | 0.8787 | 0.2425 | 0.1213 |
151 | 0.8503 | 0.2994 | 0.1497 |
152 | 0.7979 | 0.4041 | 0.2021 |
153 | 0.7379 | 0.5243 | 0.2621 |
154 | 0.7097 | 0.5805 | 0.2903 |
155 | 0.638 | 0.724 | 0.362 |
156 | 0.63 | 0.7401 | 0.37 |
157 | 0.814 | 0.372 | 0.186 |
158 | 0.7373 | 0.5253 | 0.2627 |
159 | 0.6403 | 0.7195 | 0.3597 |
160 | 0.5337 | 0.9325 | 0.4663 |
161 | 0.737 | 0.5261 | 0.263 |
162 | 0.5975 | 0.8049 | 0.4025 |
163 | 0.6179 | 0.7642 | 0.3821 |
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 | 14 | 0.0880503 | NOK |
10% type I error level | 53 | 0.333333 | NOK |
Ramsey RESET F-Test for powers (2 and 3) of fitted values |
> reset_test_fitted RESET test data: mylm RESET = 1.8095, df1 = 2, df2 = 164, p-value = 0.167 |
Ramsey RESET F-Test for powers (2 and 3) of regressors |
> reset_test_regressors RESET test data: mylm RESET = 1.8095, df1 = 2, df2 = 164, p-value = 0.167 |
Ramsey RESET F-Test for powers (2 and 3) of principal components |
> reset_test_principal_components RESET test data: mylm RESET = 1.8095, df1 = 2, df2 = 164, p-value = 0.167 |