Multiple Linear Regression - Estimated Regression Equation |
V[t] = + 0.444196 + 0.0403945W[t] + 0.118613X[t] + 0.0781361Y[t] + 0.153423Z[t] + e[t] |
Warning: you did not specify the column number of the endogenous series! The first column was selected by default. |
Multiple Linear Regression - Ordinary Least Squares | |||||
Variable | Parameter | S.D. | T-STAT H0: parameter = 0 | 2-tail p-value | 1-tail p-value |
(Intercept) | +0.4442 | 0.8302 | +5.3510e-01 | 0.5933 | 0.2967 |
W | +0.0404 | 0.0712 | +5.6730e-01 | 0.5713 | 0.2856 |
X | +0.1186 | 0.1118 | +1.0610e+00 | 0.2902 | 0.1451 |
Y | +0.07814 | 0.07117 | +1.0980e+00 | 0.2739 | 0.1369 |
Z | +0.1534 | 0.04251 | +3.6090e+00 | 0.000408 | 0.000204 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.3185 |
R-squared | 0.1014 |
Adjusted R-squared | 0.07936 |
F-TEST (value) | 4.599 |
F-TEST (DF numerator) | 4 |
F-TEST (DF denominator) | 163 |
p-value | 0.001521 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 0.8737 |
Sum Squared Residuals | 124.4 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 4 | 3.966 | 0.03384 |
2 | 5 | 4.348 | 0.6517 |
3 | 4 | 4.233 | -0.2326 |
4 | 3 | 3.807 | -0.8071 |
5 | 4 | 4.041 | -0.04144 |
6 | 5 | 4.12 | 0.8804 |
7 | 5 | 3.61 | 1.39 |
8 | 3 | 3.767 | -0.7668 |
9 | 4 | 4.036 | -0.03594 |
10 | 5 | 4.346 | 0.6544 |
11 | 5 | 3.842 | 1.158 |
12 | 4 | 3.694 | 0.3058 |
13 | 4 | 4.16 | -0.16 |
14 | 4 | 3.888 | 0.112 |
15 | 4 | 3.422 | 0.5778 |
16 | 5 | 3.384 | 1.616 |
17 | 3 | 3.966 | -0.9662 |
18 | 3 | 4.154 | -1.154 |
19 | 4 | 4.23 | -0.2297 |
20 | 5 | 3.931 | 1.069 |
21 | 4 | 3.694 | 0.3058 |
22 | 5 | 4.079 | 0.9208 |
23 | 4 | 3.92 | 0.07982 |
24 | 4 | 4.036 | -0.03594 |
25 | 3 | 3.5 | -0.5003 |
26 | 4 | 4.001 | -0.001049 |
27 | 4 | 3.497 | 0.5025 |
28 | 4 | 3.966 | 0.03384 |
29 | 4 | 4.273 | -0.273 |
30 | 3 | 3.61 | -0.6104 |
31 | 4 | 3.845 | 0.1553 |
32 | 5 | 4.311 | 0.6893 |
33 | 4 | 3.384 | 0.6156 |
34 | 4 | 3.848 | 0.1524 |
35 | 5 | 4.079 | 0.9208 |
36 | 3 | 3.576 | -0.5756 |
37 | 3 | 3.729 | -0.729 |
38 | 2 | 3.842 | -1.842 |
39 | 5 | 3.853 | 1.147 |
40 | 5 | 3.882 | 1.118 |
41 | 5 | 4.033 | 0.9668 |
42 | 4 | 3.188 | 0.8121 |
43 | 4 | 4.192 | -0.1922 |
44 | 4 | 4.114 | -0.114 |
45 | 3 | 3.382 | -0.3818 |
46 | 4 | 3.497 | 0.5025 |
47 | 4 | 3.318 | 0.6824 |
48 | 3 | 3.923 | -0.9228 |
49 | 2 | 3.428 | -1.428 |
50 | 5 | 4.117 | 0.8831 |
51 | 5 | 4.152 | 0.8485 |
52 | 5 | 4.079 | 0.9208 |
53 | 2 | 4.311 | -2.311 |
54 | 3 | 4.117 | -1.117 |
55 | 2 | 3.848 | -1.848 |
56 | 3 | 3.382 | -0.3818 |
57 | 5 | 3.694 | 1.306 |
58 | 4 | 4.001 | -0.000967 |
59 | 4 | 3.576 | 0.4244 |
60 | 5 | 4.074 | 0.9263 |
61 | 5 | 3.77 | 1.23 |
62 | 4 | 4.233 | -0.2326 |
63 | 5 | 3.393 | 1.607 |
64 | 4 | 4.039 | -0.03879 |
65 | 4 | 3.497 | 0.5025 |
66 | 5 | 3.454 | 1.546 |
67 | 3 | 4.079 | -1.079 |
68 | 2 | 3.541 | -1.541 |
69 | 5 | 3.772 | 1.228 |
70 | 3 | 3.772 | -0.7723 |
71 | 4 | 4.273 | -0.273 |
72 | 4 | 3.966 | 0.03384 |
73 | 4 | 3.694 | 0.3058 |
74 | 4 | 3.998 | 0.0018 |
75 | 4 | 3.622 | 0.3784 |
76 | 5 | 4.192 | 0.8078 |
77 | 3 | 3.885 | -0.8852 |
78 | 2 | 3.769 | -1.769 |
79 | 5 | 4.079 | 0.9208 |
80 | 4 | 4.079 | -0.07918 |
81 | 1 | 3.769 | -2.769 |
82 | 4 | 3.845 | 0.1553 |
83 | 5 | 3.839 | 1.161 |
84 | 4 | 4.389 | -0.3887 |
85 | 5 | 3.463 | 1.537 |
86 | 4 | 4.233 | -0.2325 |
87 | 5 | 4.308 | 0.6921 |
88 | 3 | 4.16 | -1.16 |
89 | 5 | 3.81 | 1.19 |
90 | 5 | 3.848 | 1.152 |
91 | 4 | 3.654 | 0.3464 |
92 | 4 | 4.001 | -0.000967 |
93 | 4 | 3.764 | 0.2361 |
94 | 4 | 4.154 | -0.1545 |
95 | 3 | 4.195 | -1.195 |
96 | 4 | 4.154 | -0.1545 |
97 | 4 | 4.001 | -0.001049 |
98 | 5 | 4.232 | 0.7676 |
99 | 5 | 3.882 | 1.118 |
100 | 3 | 3.613 | -0.6134 |
101 | 5 | 4.386 | 0.614 |
102 | 4 | 4.273 | -0.273 |
103 | 2 | 3.764 | -1.764 |
104 | 3 | 3.5 | -0.5003 |
105 | 5 | 4.348 | 0.6517 |
106 | 4 | 3.966 | 0.03384 |
107 | 4 | 4.041 | -0.04144 |
108 | 4 | 4.12 | -0.1196 |
109 | 4 | 4.16 | -0.16 |
110 | 3 | 3.845 | -0.8447 |
111 | 4 | 3.5 | 0.4997 |
112 | 4 | 3.654 | 0.3463 |
113 | 3 | 3.689 | -0.6885 |
114 | 5 | 3.769 | 1.231 |
115 | 4 | 3.769 | 0.2306 |
116 | 5 | 4.039 | 0.9612 |
117 | 5 | 4.313 | 0.6866 |
118 | 5 | 4.499 | 0.5009 |
119 | 3 | 3.807 | -0.8072 |
120 | 4 | 3.807 | 0.1928 |
121 | 3 | 3.729 | -0.729 |
122 | 4 | 3.923 | 0.07709 |
123 | 4 | 4.273 | -0.273 |
124 | 4 | 3.998 | 0.001882 |
125 | 4 | 3.888 | 0.112 |
126 | 5 | 3.926 | 1.074 |
127 | 4 | 3.845 | 0.1553 |
128 | 3 | 3.581 | -0.5812 |
129 | 4 | 4.001 | -0.001049 |
130 | 2 | 3.769 | -1.769 |
131 | 4 | 4.16 | -0.16 |
132 | 4 | 4.23 | -0.2297 |
133 | 2 | 3.619 | -1.619 |
134 | 2 | 3.225 | -1.225 |
135 | 4 | 3.848 | 0.1524 |
136 | 4 | 4.227 | -0.2269 |
137 | 2 | 2.921 | -0.9214 |
138 | 4 | 3.769 | 0.2305 |
139 | 5 | 4.268 | 0.7325 |
140 | 4 | 3.998 | 0.001882 |
141 | 4 | 4.12 | -0.1196 |
142 | 3 | 3.966 | -0.9662 |
143 | 4 | 4.007 | -0.006551 |
144 | 3 | 3.883 | -0.8825 |
145 | 4 | 3.961 | 0.03935 |
146 | 2 | 4.154 | -2.154 |
147 | 5 | 4.233 | 0.7674 |
148 | 4 | 3.961 | 0.03935 |
149 | 4 | 4.351 | -0.3511 |
150 | 3 | 3.382 | -0.3818 |
151 | 4 | 4.233 | -0.2326 |
152 | 5 | 3.853 | 1.147 |
153 | 4 | 3.619 | 0.3811 |
154 | 2 | 4.004 | -2.004 |
155 | 4 | 4.044 | -0.04429 |
156 | 5 | 4.039 | 0.9612 |
157 | 4 | 3.853 | 0.1469 |
158 | 2 | 3.769 | -1.769 |
159 | 5 | 4.079 | 0.9208 |
160 | 4 | 4.004 | -0.003702 |
161 | 5 | 3.92 | 1.08 |
162 | 3 | 4.076 | -1.076 |
163 | 5 | 4.195 | 0.8051 |
164 | 4 | 4.351 | -0.3511 |
165 | 3 | 3.885 | -0.8853 |
166 | 4 | 4.085 | -0.08469 |
167 | 4 | 3.729 | 0.271 |
168 | 3 | 3.078 | -0.07766 |
Goldfeld-Quandt test for Heteroskedasticity | |||
p-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
8 | 0.471 | 0.942 | 0.529 |
9 | 0.4559 | 0.9118 | 0.5441 |
10 | 0.4909 | 0.9819 | 0.5091 |
11 | 0.4214 | 0.8427 | 0.5786 |
12 | 0.3556 | 0.7112 | 0.6444 |
13 | 0.2761 | 0.5521 | 0.7239 |
14 | 0.1927 | 0.3855 | 0.8073 |
15 | 0.1431 | 0.2861 | 0.8569 |
16 | 0.1286 | 0.2572 | 0.8714 |
17 | 0.1273 | 0.2547 | 0.8727 |
18 | 0.2756 | 0.5511 | 0.7244 |
19 | 0.2563 | 0.5127 | 0.7437 |
20 | 0.3745 | 0.749 | 0.6255 |
21 | 0.3049 | 0.6098 | 0.6951 |
22 | 0.3226 | 0.6452 | 0.6774 |
23 | 0.2585 | 0.517 | 0.7415 |
24 | 0.2125 | 0.4251 | 0.7875 |
25 | 0.2096 | 0.4193 | 0.7904 |
26 | 0.1654 | 0.3308 | 0.8346 |
27 | 0.1288 | 0.2576 | 0.8712 |
28 | 0.09637 | 0.1927 | 0.9036 |
29 | 0.07241 | 0.1448 | 0.9276 |
30 | 0.07461 | 0.1492 | 0.9254 |
31 | 0.05556 | 0.1111 | 0.9444 |
32 | 0.0584 | 0.1168 | 0.9416 |
33 | 0.04358 | 0.08716 | 0.9564 |
34 | 0.03147 | 0.06294 | 0.9685 |
35 | 0.0321 | 0.06421 | 0.9679 |
36 | 0.03245 | 0.0649 | 0.9676 |
37 | 0.03406 | 0.06811 | 0.9659 |
38 | 0.1064 | 0.2129 | 0.8936 |
39 | 0.1047 | 0.2094 | 0.8953 |
40 | 0.129 | 0.2581 | 0.871 |
41 | 0.16 | 0.32 | 0.84 |
42 | 0.1494 | 0.2988 | 0.8506 |
43 | 0.1224 | 0.2448 | 0.8776 |
44 | 0.09708 | 0.1942 | 0.9029 |
45 | 0.08733 | 0.1747 | 0.9127 |
46 | 0.07081 | 0.1416 | 0.9292 |
47 | 0.05806 | 0.1161 | 0.9419 |
48 | 0.06418 | 0.1284 | 0.9358 |
49 | 0.1175 | 0.2351 | 0.8825 |
50 | 0.1107 | 0.2214 | 0.8893 |
51 | 0.115 | 0.2299 | 0.885 |
52 | 0.1107 | 0.2214 | 0.8893 |
53 | 0.335 | 0.67 | 0.665 |
54 | 0.3614 | 0.7228 | 0.6386 |
55 | 0.5628 | 0.8744 | 0.4372 |
56 | 0.5281 | 0.9437 | 0.4719 |
57 | 0.5816 | 0.8367 | 0.4184 |
58 | 0.5343 | 0.9314 | 0.4657 |
59 | 0.4951 | 0.9903 | 0.5049 |
60 | 0.4962 | 0.9924 | 0.5038 |
61 | 0.5374 | 0.9251 | 0.4626 |
62 | 0.4941 | 0.9881 | 0.5059 |
63 | 0.5801 | 0.8397 | 0.4199 |
64 | 0.5349 | 0.9302 | 0.4651 |
65 | 0.5009 | 0.9981 | 0.4991 |
66 | 0.6045 | 0.7911 | 0.3955 |
67 | 0.6308 | 0.7385 | 0.3692 |
68 | 0.7228 | 0.5543 | 0.2772 |
69 | 0.7656 | 0.4688 | 0.2344 |
70 | 0.76 | 0.4799 | 0.24 |
71 | 0.727 | 0.546 | 0.273 |
72 | 0.688 | 0.6239 | 0.312 |
73 | 0.6522 | 0.6957 | 0.3478 |
74 | 0.6108 | 0.7784 | 0.3892 |
75 | 0.5794 | 0.8412 | 0.4206 |
76 | 0.572 | 0.8559 | 0.428 |
77 | 0.5799 | 0.8403 | 0.4201 |
78 | 0.7098 | 0.5803 | 0.2902 |
79 | 0.7139 | 0.5721 | 0.2861 |
80 | 0.6746 | 0.6508 | 0.3254 |
81 | 0.9254 | 0.1491 | 0.07455 |
82 | 0.909 | 0.1821 | 0.09103 |
83 | 0.9248 | 0.1503 | 0.07516 |
84 | 0.9115 | 0.1769 | 0.08847 |
85 | 0.9479 | 0.1043 | 0.05213 |
86 | 0.9356 | 0.1289 | 0.06445 |
87 | 0.9298 | 0.1404 | 0.0702 |
88 | 0.9414 | 0.1171 | 0.05857 |
89 | 0.9549 | 0.09011 | 0.04505 |
90 | 0.9654 | 0.06915 | 0.03458 |
91 | 0.9604 | 0.07928 | 0.03964 |
92 | 0.9497 | 0.1005 | 0.05026 |
93 | 0.9402 | 0.1196 | 0.05981 |
94 | 0.9259 | 0.1483 | 0.07415 |
95 | 0.9412 | 0.1175 | 0.05877 |
96 | 0.9272 | 0.1457 | 0.07285 |
97 | 0.9098 | 0.1805 | 0.09025 |
98 | 0.9063 | 0.1874 | 0.09372 |
99 | 0.928 | 0.144 | 0.072 |
100 | 0.9191 | 0.1618 | 0.08092 |
101 | 0.9088 | 0.1823 | 0.09117 |
102 | 0.8912 | 0.2176 | 0.1088 |
103 | 0.9392 | 0.1216 | 0.06082 |
104 | 0.9273 | 0.1455 | 0.07275 |
105 | 0.9189 | 0.1622 | 0.08111 |
106 | 0.8996 | 0.2008 | 0.1004 |
107 | 0.8769 | 0.2462 | 0.1231 |
108 | 0.8512 | 0.2975 | 0.1488 |
109 | 0.8224 | 0.3552 | 0.1776 |
110 | 0.8122 | 0.3755 | 0.1878 |
111 | 0.8064 | 0.3871 | 0.1936 |
112 | 0.7901 | 0.4199 | 0.2099 |
113 | 0.7644 | 0.4712 | 0.2356 |
114 | 0.8326 | 0.3348 | 0.1674 |
115 | 0.8142 | 0.3716 | 0.1858 |
116 | 0.8235 | 0.3531 | 0.1765 |
117 | 0.8118 | 0.3763 | 0.1882 |
118 | 0.7835 | 0.433 | 0.2165 |
119 | 0.7747 | 0.4506 | 0.2253 |
120 | 0.7383 | 0.5234 | 0.2617 |
121 | 0.7103 | 0.5793 | 0.2897 |
122 | 0.6655 | 0.6689 | 0.3345 |
123 | 0.6216 | 0.7568 | 0.3784 |
124 | 0.5754 | 0.8492 | 0.4246 |
125 | 0.5277 | 0.9446 | 0.4723 |
126 | 0.5721 | 0.8557 | 0.4279 |
127 | 0.5364 | 0.9272 | 0.4636 |
128 | 0.4931 | 0.9861 | 0.5069 |
129 | 0.4394 | 0.8789 | 0.5606 |
130 | 0.5836 | 0.8329 | 0.4164 |
131 | 0.5284 | 0.9431 | 0.4716 |
132 | 0.4726 | 0.9453 | 0.5274 |
133 | 0.5851 | 0.8298 | 0.4149 |
134 | 0.566 | 0.868 | 0.434 |
135 | 0.5094 | 0.9812 | 0.4906 |
136 | 0.465 | 0.93 | 0.535 |
137 | 0.4193 | 0.8386 | 0.5807 |
138 | 0.3642 | 0.7284 | 0.6358 |
139 | 0.3482 | 0.6965 | 0.6518 |
140 | 0.3114 | 0.6229 | 0.6886 |
141 | 0.2575 | 0.5151 | 0.7425 |
142 | 0.2588 | 0.5177 | 0.7412 |
143 | 0.2085 | 0.417 | 0.7915 |
144 | 0.2025 | 0.405 | 0.7975 |
145 | 0.1579 | 0.3158 | 0.8421 |
146 | 0.4857 | 0.9715 | 0.5143 |
147 | 0.4392 | 0.8784 | 0.5608 |
148 | 0.3843 | 0.7685 | 0.6157 |
149 | 0.3228 | 0.6455 | 0.6772 |
150 | 0.2558 | 0.5117 | 0.7442 |
151 | 0.2215 | 0.4431 | 0.7785 |
152 | 0.3503 | 0.7006 | 0.6497 |
153 | 0.2888 | 0.5777 | 0.7112 |
154 | 0.8452 | 0.3096 | 0.1548 |
155 | 0.7735 | 0.4531 | 0.2265 |
156 | 0.7242 | 0.5516 | 0.2758 |
157 | 0.7409 | 0.5181 | 0.2591 |
158 | 0.7334 | 0.5331 | 0.2666 |
159 | 0.5967 | 0.8067 | 0.4033 |
160 | 0.4404 | 0.8808 | 0.5596 |
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 | 8 | 0.0522876 | OK |
Ramsey RESET F-Test for powers (2 and 3) of fitted values |
> reset_test_fitted RESET test data: mylm RESET = 0.70278, df1 = 2, df2 = 161, p-value = 0.4967 |
Ramsey RESET F-Test for powers (2 and 3) of regressors |
> reset_test_regressors RESET test data: mylm RESET = 1.3206, df1 = 8, df2 = 155, p-value = 0.237 |
Ramsey RESET F-Test for powers (2 and 3) of principal components |
> reset_test_principal_components RESET test data: mylm RESET = 1.6602, df1 = 2, df2 = 161, p-value = 0.1933 |
Variance Inflation Factors (Multicollinearity) |
> vif W X Y Z 1.013755 1.074113 1.020744 1.058907 |