Multiple Linear Regression - Estimated Regression Equation |
ITHSUM[t] = + 14.3562 + 0.361175KVDD1[t] + 0.0725785KVDD2[t] + 0.110083KVDD3[t] -0.0334588KVDD4[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) | +14.36 | 1.365 | +1.0520e+01 | 4.433e-20 | 2.216e-20 |
KVDD1 | +0.3612 | 0.2705 | +1.3350e+00 | 0.1837 | 0.09183 |
KVDD2 | +0.07258 | 0.2208 | +3.2880e-01 | 0.7428 | 0.3714 |
KVDD3 | +0.1101 | 0.2143 | +5.1360e-01 | 0.6082 | 0.3041 |
KVDD4 | -0.03346 | 0.2264 | -1.4780e-01 | 0.8827 | 0.4414 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.1276 |
R-squared | 0.01628 |
Adjusted R-squared | -0.007861 |
F-TEST (value) | 0.6744 |
F-TEST (DF numerator) | 4 |
F-TEST (DF denominator) | 163 |
p-value | 0.6107 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 2.501 |
Sum Squared Residuals | 1019 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 14 | 16.76 | -2.759 |
2 | 19 | 16.76 | 2.241 |
3 | 17 | 16.28 | 0.7181 |
4 | 17 | 16.25 | 0.7515 |
5 | 15 | 16.79 | -1.792 |
6 | 20 | 16.72 | 3.28 |
7 | 15 | 16.57 | -1.572 |
8 | 19 | 16.54 | 2.461 |
9 | 15 | 16.39 | -1.394 |
10 | 15 | 16.32 | -1.321 |
11 | 19 | 16.35 | 2.645 |
12 | 16 | 16.72 | -0.7157 |
13 | 20 | 16.87 | 3.131 |
14 | 18 | 16.8 | 1.202 |
15 | 15 | 16.29 | -1.288 |
16 | 14 | 16.54 | -2.541 |
17 | 20 | 16.1 | 3.897 |
18 | 16 | 16.46 | -0.4605 |
19 | 16 | 16.65 | -0.6528 |
20 | 16 | 16.69 | -0.6863 |
21 | 10 | 15.52 | -5.52 |
22 | 19 | 15.68 | 3.325 |
23 | 19 | 16.14 | 2.862 |
24 | 16 | 16.03 | -0.03237 |
25 | 15 | 16.21 | -1.215 |
26 | 18 | 16.72 | 1.284 |
27 | 17 | 16.29 | 0.7124 |
28 | 19 | 16.68 | 2.319 |
29 | 17 | 16.36 | 0.6414 |
30 | 14 | 16.65 | -2.649 |
31 | 19 | 16.4 | 2.602 |
32 | 20 | 16.29 | 3.712 |
33 | 5 | 16.33 | -11.33 |
34 | 19 | 16.65 | 2.351 |
35 | 16 | 16.65 | -0.6488 |
36 | 15 | 16.62 | -1.615 |
37 | 16 | 16.65 | -0.6488 |
38 | 18 | 15.38 | 2.617 |
39 | 16 | 16.47 | -0.4687 |
40 | 15 | 16.29 | -1.288 |
41 | 17 | 15.92 | 1.078 |
42 | 14 | 16.5 | -2.5 |
43 | 20 | 16.61 | 3.394 |
44 | 19 | 16.62 | 2.385 |
45 | 7 | 16.1 | -9.105 |
46 | 13 | 16.18 | -3.176 |
47 | 16 | 16.8 | -0.7964 |
48 | 16 | 16.69 | -0.6863 |
49 | 16 | 16.87 | -0.8689 |
50 | 18 | 16.14 | 1.862 |
51 | 18 | 16.33 | 1.675 |
52 | 16 | 16.58 | -0.5762 |
53 | 17 | 16.58 | 0.4238 |
54 | 19 | 16.47 | 2.534 |
55 | 16 | 16.33 | -0.3267 |
56 | 19 | 16.54 | 2.461 |
57 | 13 | 16.83 | -3.826 |
58 | 16 | 16.33 | -0.3251 |
59 | 13 | 16.25 | -3.254 |
60 | 12 | 16.5 | -4.496 |
61 | 17 | 16.24 | 0.7557 |
62 | 17 | 16.29 | 0.7124 |
63 | 17 | 16.25 | 0.7515 |
64 | 16 | 16.47 | -0.4661 |
65 | 16 | 15.93 | 0.07357 |
66 | 14 | 15.89 | -1.891 |
67 | 16 | 16.62 | -0.6153 |
68 | 13 | 16.5 | -3.504 |
69 | 16 | 16.4 | -0.3977 |
70 | 14 | 16.65 | -2.649 |
71 | 20 | 16.76 | 3.241 |
72 | 12 | 16.4 | -4.398 |
73 | 13 | 16.65 | -3.649 |
74 | 18 | 16.14 | 1.858 |
75 | 14 | 16.51 | -2.508 |
76 | 19 | 16.03 | 2.968 |
77 | 18 | 16.83 | 1.169 |
78 | 14 | 16.39 | -2.394 |
79 | 18 | 16.18 | 1.824 |
80 | 19 | 16.35 | 2.645 |
81 | 15 | 16.39 | -1.392 |
82 | 14 | 16.39 | -2.392 |
83 | 17 | 15.53 | 1.474 |
84 | 19 | 16.51 | 2.492 |
85 | 13 | 16.29 | -3.288 |
86 | 19 | 16.69 | 2.314 |
87 | 18 | 16.21 | 1.785 |
88 | 20 | 16.87 | 3.131 |
89 | 15 | 16.4 | -1.398 |
90 | 15 | 16.25 | -1.253 |
91 | 15 | 16.03 | -1.031 |
92 | 20 | 16.36 | 3.641 |
93 | 15 | 15.45 | -0.4495 |
94 | 19 | 16.32 | 2.679 |
95 | 18 | 16.76 | 1.241 |
96 | 18 | 15.89 | 2.107 |
97 | 15 | 16.29 | -1.288 |
98 | 20 | 16.91 | 3.092 |
99 | 17 | 15.6 | 1.401 |
100 | 12 | 16.32 | -4.323 |
101 | 18 | 16.65 | 1.351 |
102 | 19 | 16.73 | 2.275 |
103 | 20 | 16.1 | 3.901 |
104 | 13 | 16.25 | -3.248 |
105 | 17 | 16.69 | 0.3137 |
106 | 15 | 16.65 | -1.653 |
107 | 16 | 16.4 | -0.3977 |
108 | 18 | 16.36 | 1.636 |
109 | 18 | 16.84 | 1.165 |
110 | 14 | 16.73 | -2.725 |
111 | 15 | 16.58 | -1.576 |
112 | 12 | 16.21 | -4.215 |
113 | 17 | 16.58 | 0.4238 |
114 | 14 | 16.25 | -2.253 |
115 | 18 | 16.69 | 1.314 |
116 | 17 | 16.03 | 0.9676 |
117 | 17 | 16.84 | 0.1645 |
118 | 20 | 16.58 | 3.422 |
119 | 16 | 16.07 | -0.07149 |
120 | 14 | 16.1 | -2.105 |
121 | 15 | 16.21 | -1.215 |
122 | 18 | 16.5 | 1.496 |
123 | 20 | 16.65 | 3.347 |
124 | 17 | 16.33 | 0.6749 |
125 | 17 | 16.33 | 0.6749 |
126 | 17 | 16.65 | 0.3512 |
127 | 17 | 16.76 | 0.2411 |
128 | 15 | 16.39 | -1.392 |
129 | 17 | 16.29 | 0.7124 |
130 | 18 | 16.14 | 1.863 |
131 | 17 | 16.58 | 0.4196 |
132 | 20 | 16.79 | 3.208 |
133 | 15 | 16.54 | -1.543 |
134 | 16 | 16.43 | -0.4271 |
135 | 15 | 16.29 | -1.288 |
136 | 18 | 16.25 | 1.752 |
137 | 11 | 16.4 | -5.398 |
138 | 15 | 15.96 | -0.9599 |
139 | 18 | 16.18 | 1.822 |
140 | 20 | 16.65 | 3.347 |
141 | 19 | 16.29 | 2.714 |
142 | 14 | 16.46 | -2.465 |
143 | 16 | 16.76 | -0.7629 |
144 | 15 | 15.74 | -0.7438 |
145 | 17 | 16.18 | 0.8225 |
146 | 18 | 15.13 | 2.874 |
147 | 20 | 16.54 | 3.457 |
148 | 17 | 16.21 | 0.789 |
149 | 18 | 16.79 | 1.208 |
150 | 15 | 15.78 | -0.7772 |
151 | 16 | 16.29 | -0.2876 |
152 | 11 | 16.4 | -5.398 |
153 | 15 | 16.21 | -1.215 |
154 | 18 | 16.14 | 1.858 |
155 | 17 | 16.76 | 0.2411 |
156 | 16 | 16.39 | -0.3935 |
157 | 12 | 16.76 | -4.763 |
158 | 19 | 16.79 | 2.208 |
159 | 18 | 16.25 | 1.752 |
160 | 15 | 16.72 | -1.724 |
161 | 17 | 16.54 | 0.4613 |
162 | 19 | 16.15 | 2.853 |
163 | 18 | 16.14 | 1.857 |
164 | 19 | 16.4 | 2.602 |
165 | 16 | 16.28 | -0.2819 |
166 | 16 | 16.84 | -0.8355 |
167 | 16 | 16.29 | -0.2876 |
168 | 14 | 16.25 | -2.248 |
Goldfeld-Quandt test for Heteroskedasticity | |||
p-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
8 | 0.5433 | 0.9134 | 0.4567 |
9 | 0.7753 | 0.4494 | 0.2247 |
10 | 0.6737 | 0.6527 | 0.3263 |
11 | 0.5882 | 0.8235 | 0.4118 |
12 | 0.4774 | 0.9548 | 0.5226 |
13 | 0.4365 | 0.873 | 0.5635 |
14 | 0.3395 | 0.679 | 0.6605 |
15 | 0.3452 | 0.6904 | 0.6548 |
16 | 0.3308 | 0.6615 | 0.6692 |
17 | 0.2829 | 0.5658 | 0.7171 |
18 | 0.2161 | 0.4322 | 0.7839 |
19 | 0.1598 | 0.3196 | 0.8402 |
20 | 0.117 | 0.234 | 0.883 |
21 | 0.3662 | 0.7323 | 0.6338 |
22 | 0.5391 | 0.9217 | 0.4609 |
23 | 0.5553 | 0.8894 | 0.4447 |
24 | 0.4846 | 0.9693 | 0.5154 |
25 | 0.4513 | 0.9025 | 0.5487 |
26 | 0.401 | 0.802 | 0.599 |
27 | 0.3401 | 0.6802 | 0.6599 |
28 | 0.3606 | 0.7212 | 0.6394 |
29 | 0.3023 | 0.6046 | 0.6977 |
30 | 0.3365 | 0.673 | 0.6635 |
31 | 0.3099 | 0.6198 | 0.6901 |
32 | 0.3375 | 0.675 | 0.6625 |
33 | 0.9887 | 0.02257 | 0.01129 |
34 | 0.9866 | 0.02671 | 0.01335 |
35 | 0.9822 | 0.03563 | 0.01781 |
36 | 0.9789 | 0.0422 | 0.0211 |
37 | 0.9721 | 0.05586 | 0.02793 |
38 | 0.9699 | 0.06016 | 0.03008 |
39 | 0.9598 | 0.0803 | 0.04015 |
40 | 0.9526 | 0.09483 | 0.04741 |
41 | 0.9409 | 0.1182 | 0.05912 |
42 | 0.9394 | 0.1212 | 0.06061 |
43 | 0.9444 | 0.1112 | 0.05558 |
44 | 0.9401 | 0.1198 | 0.0599 |
45 | 0.9983 | 0.003366 | 0.001683 |
46 | 0.9985 | 0.003085 | 0.001542 |
47 | 0.9978 | 0.004451 | 0.002225 |
48 | 0.9968 | 0.006365 | 0.003182 |
49 | 0.9956 | 0.008756 | 0.004378 |
50 | 0.9948 | 0.01042 | 0.005211 |
51 | 0.9938 | 0.01239 | 0.006197 |
52 | 0.9915 | 0.01706 | 0.008532 |
53 | 0.9885 | 0.02304 | 0.01152 |
54 | 0.9885 | 0.023 | 0.0115 |
55 | 0.985 | 0.03006 | 0.01503 |
56 | 0.9841 | 0.03181 | 0.0159 |
57 | 0.9894 | 0.02122 | 0.01061 |
58 | 0.9857 | 0.02857 | 0.01428 |
59 | 0.9883 | 0.02335 | 0.01167 |
60 | 0.9944 | 0.01114 | 0.00557 |
61 | 0.9929 | 0.01429 | 0.007144 |
62 | 0.9904 | 0.01914 | 0.00957 |
63 | 0.9874 | 0.0252 | 0.0126 |
64 | 0.9834 | 0.03329 | 0.01664 |
65 | 0.978 | 0.04395 | 0.02197 |
66 | 0.9748 | 0.05042 | 0.02521 |
67 | 0.9678 | 0.06449 | 0.03225 |
68 | 0.9745 | 0.05099 | 0.0255 |
69 | 0.9671 | 0.06587 | 0.03293 |
70 | 0.968 | 0.06407 | 0.03203 |
71 | 0.9729 | 0.0542 | 0.0271 |
72 | 0.9839 | 0.03216 | 0.01608 |
73 | 0.9885 | 0.02307 | 0.01154 |
74 | 0.987 | 0.02607 | 0.01303 |
75 | 0.9866 | 0.02671 | 0.01335 |
76 | 0.988 | 0.0239 | 0.01195 |
77 | 0.985 | 0.02995 | 0.01497 |
78 | 0.9848 | 0.03044 | 0.01522 |
79 | 0.9827 | 0.0347 | 0.01735 |
80 | 0.983 | 0.03409 | 0.01705 |
81 | 0.9797 | 0.04067 | 0.02034 |
82 | 0.9801 | 0.03987 | 0.01994 |
83 | 0.9764 | 0.04716 | 0.02358 |
84 | 0.9766 | 0.04675 | 0.02338 |
85 | 0.9811 | 0.03785 | 0.01893 |
86 | 0.9801 | 0.03984 | 0.01992 |
87 | 0.9772 | 0.04555 | 0.02278 |
88 | 0.9801 | 0.03972 | 0.01986 |
89 | 0.9762 | 0.04763 | 0.02381 |
90 | 0.9711 | 0.05777 | 0.02889 |
91 | 0.9651 | 0.06972 | 0.03486 |
92 | 0.9731 | 0.05376 | 0.02688 |
93 | 0.9658 | 0.06842 | 0.03421 |
94 | 0.9664 | 0.06721 | 0.0336 |
95 | 0.9592 | 0.08164 | 0.04082 |
96 | 0.957 | 0.08605 | 0.04303 |
97 | 0.9487 | 0.1025 | 0.05127 |
98 | 0.9565 | 0.08693 | 0.04346 |
99 | 0.9493 | 0.1015 | 0.05074 |
100 | 0.974 | 0.0521 | 0.02605 |
101 | 0.9679 | 0.06415 | 0.03208 |
102 | 0.9675 | 0.06504 | 0.03252 |
103 | 0.9753 | 0.0494 | 0.0247 |
104 | 0.9812 | 0.03751 | 0.01875 |
105 | 0.9751 | 0.04985 | 0.02493 |
106 | 0.9712 | 0.05761 | 0.0288 |
107 | 0.9624 | 0.07519 | 0.0376 |
108 | 0.9584 | 0.08316 | 0.04158 |
109 | 0.9515 | 0.09696 | 0.04848 |
110 | 0.9532 | 0.09365 | 0.04683 |
111 | 0.9489 | 0.1023 | 0.05114 |
112 | 0.9728 | 0.05435 | 0.02718 |
113 | 0.9642 | 0.07157 | 0.03579 |
114 | 0.9646 | 0.0708 | 0.0354 |
115 | 0.956 | 0.08796 | 0.04398 |
116 | 0.9439 | 0.1123 | 0.05614 |
117 | 0.9286 | 0.1429 | 0.07145 |
118 | 0.945 | 0.11 | 0.05502 |
119 | 0.9293 | 0.1413 | 0.07065 |
120 | 0.9324 | 0.1353 | 0.06763 |
121 | 0.9221 | 0.1558 | 0.0779 |
122 | 0.904 | 0.1919 | 0.09597 |
123 | 0.9226 | 0.1549 | 0.07745 |
124 | 0.9028 | 0.1945 | 0.09722 |
125 | 0.8795 | 0.241 | 0.1205 |
126 | 0.8502 | 0.2997 | 0.1498 |
127 | 0.8174 | 0.3653 | 0.1826 |
128 | 0.8 | 0.4 | 0.2 |
129 | 0.7633 | 0.4734 | 0.2367 |
130 | 0.7249 | 0.5502 | 0.2751 |
131 | 0.6991 | 0.6017 | 0.3009 |
132 | 0.744 | 0.5121 | 0.256 |
133 | 0.7205 | 0.559 | 0.2795 |
134 | 0.6691 | 0.6618 | 0.3309 |
135 | 0.6254 | 0.7492 | 0.3746 |
136 | 0.5841 | 0.8317 | 0.4159 |
137 | 0.7571 | 0.4858 | 0.2429 |
138 | 0.7176 | 0.5647 | 0.2824 |
139 | 0.6799 | 0.6401 | 0.3201 |
140 | 0.7368 | 0.5263 | 0.2632 |
141 | 0.738 | 0.524 | 0.262 |
142 | 0.7371 | 0.5258 | 0.2629 |
143 | 0.6784 | 0.6432 | 0.3216 |
144 | 0.6408 | 0.7184 | 0.3592 |
145 | 0.5729 | 0.8541 | 0.4271 |
146 | 0.5406 | 0.9187 | 0.4594 |
147 | 0.6244 | 0.7512 | 0.3756 |
148 | 0.5502 | 0.8996 | 0.4498 |
149 | 0.4971 | 0.9941 | 0.5029 |
150 | 0.4619 | 0.9239 | 0.5381 |
151 | 0.3808 | 0.7615 | 0.6192 |
152 | 0.7104 | 0.5792 | 0.2896 |
153 | 0.6894 | 0.6212 | 0.3106 |
154 | 0.614 | 0.772 | 0.386 |
155 | 0.5253 | 0.9494 | 0.4747 |
156 | 0.4165 | 0.8331 | 0.5835 |
157 | 0.6457 | 0.7085 | 0.3543 |
158 | 0.7903 | 0.4195 | 0.2097 |
159 | 0.7328 | 0.5344 | 0.2672 |
160 | 0.5729 | 0.8542 | 0.4271 |
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | |||
Description | # significant tests | % significant tests | OK/NOK |
1% type I error level | 5 | 0.03268 | NOK |
5% type I error level | 46 | 0.300654 | NOK |
10% type I error level | 76 | 0.496732 | NOK |
Ramsey RESET F-Test for powers (2 and 3) of fitted values |
> reset_test_fitted RESET test data: mylm RESET = 2.1717, df1 = 2, df2 = 161, p-value = 0.1173 |
Ramsey RESET F-Test for powers (2 and 3) of regressors |
> reset_test_regressors RESET test data: mylm RESET = 2.1026, df1 = 8, df2 = 155, p-value = 0.03863 |
Ramsey RESET F-Test for powers (2 and 3) of principal components |
> reset_test_principal_components RESET test data: mylm RESET = 1.5274, df1 = 2, df2 = 161, p-value = 0.2202 |
Variance Inflation Factors (Multicollinearity) |
> vif KVDD1 KVDD2 KVDD3 KVDD4 1.141081 1.064463 1.077699 1.144094 |