Multiple Linear Regression - Estimated Regression Equation
TVDCSUM[t] = + 14.2885 + 0.126562KVDD1[t] -0.0102548KVDD2[t] -0.0640709KVDD3[t] + 0.212575KVDD4[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0		2-tail p-value1-tail p-value
(Intercept)+14.29 1.461+9.7800e+00 9.112e-16 4.556e-16
KVDD1+0.1266 0.2696+4.6950e-01 0.6399 0.3199
KVDD2-0.01026 0.2021-5.0750e-02 0.9596 0.4798
KVDD3-0.06407 0.2193-2.9210e-01 0.7709 0.3854
KVDD4+0.2126 0.2296+9.2590e-01 0.357 0.1785


Multiple Linear Regression - Regression Statistics
Multiple R 0.1177
R-squared 0.01386
Adjusted R-squared-0.03046
F-TEST (value) 0.3128
F-TEST (DF numerator)4
F-TEST (DF denominator)89
p-value 0.8687
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation 1.953
Sum Squared Residuals 339.4


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast		Residuals
Prediction Error
1 13 15.47-2.474
2 17 15 2.003
3 16 15.27 0.728
4 17 15.63 1.367
5 17 14.99 2.013
6 15 15.11-0.1132
7 16 15.41 0.5898
8 14 15.68-1.677
9 16 15.41 0.5882
10 17 15.51 1.495
11 16 15.53 0.4714
12 16 15.11 0.8868
13 15 15.41-0.4118
14 16 15.07 0.9303
15 16 15.15 0.8546
16 13 15.54-2.538
17 15 15.35-0.3478
18 17 15.41 1.588
19 13 15.54-2.538
20 17 15.54 1.462
21 14 15.54-1.538
22 14 15.23-1.233
23 18 15.08 2.919
24 17 15.56 1.44
25 13 15.4-2.4
26 16 15.18 0.8227
27 15 15.75-0.751
28 15 15.49-0.4862
29 15 15.42-0.4205
30 13 15.48-2.485
31 17 15.27 1.726
32 11 15.55-4.549
33 14 15.61-1.613
34 13 15.61-2.614
35 17 15.24 1.759
36 16 15.48 0.5153
37 16 15.41 0.5882
38 15 15.61-0.6127
39 12 15.29-3.285
40 17 15.24 1.758
41 14 15.75-1.751
42 14 15.12-1.125
43 16 15.35 0.6522
44 15 15.28-0.2837
45 16 15.5 0.5036
46 14 15.46-1.464
47 15 15.19-0.189
48 17 15.22 1.78
49 10 14.93-4.933
50 20 15.41 4.588
51 17 15.48 1.515
52 18 15.42 2.578
53 17 15.35 1.652
54 14 15.37-1.368
55 17 15.15 1.855
56 17 15.2 1.801
57 16 15.5 0.5022
58 18 15.41 2.588
59 18 15.61 2.387
60 16 14.95 1.054
61 15 15.69-0.6869
62 13 15.07-2.071
63 12 15.55-3.549
64 16 15.48 0.5154
65 16 15.5 0.5036
66 16 15.8 0.1952
67 14 15.7-1.699
68 15 15.49-0.4862
69 14 15.42-1.422
70 15 15.7-0.6971
71 15 15.36-0.358
72 16 15.54 0.4616
73 11 15.02-4.017
74 18 15.26 2.738
75 11 14.98-3.976
76 18 15.21 2.791
77 15 15.07-0.07269
78 19 15.48 3.524
79 17 15.7 1.303
80 14 14.92-0.9226
81 13 15.36-2.36
82 17 15.48 1.524
83 14 14.63-0.6275
84 19 15.76 3.239
85 14 15.26-1.263
86 16 15.41 0.5882
87 15 15.42-0.4221
88 12 15.43-3.432
89 17 15.62 1.377
90 15 15.43-0.4308
91 18 15.6 2.398
92 15 15.59-0.5911
93 16 15.62 0.3772
94 16 15.21 0.7905


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
8 0.2333 0.4667 0.7667
9 0.1117 0.2234 0.8883
10 0.05294 0.1059 0.9471
11 0.07394 0.1479 0.9261
12 0.03616 0.07232 0.9638
13 0.01664 0.03328 0.9834
14 0.01172 0.02345 0.9883
15 0.00529 0.01058 0.9947
16 0.008432 0.01686 0.9916
17 0.003945 0.007891 0.9961
18 0.00617 0.01234 0.9938
19 0.007077 0.01415 0.9929
20 0.01641 0.03282 0.9836
21 0.0108 0.02161 0.9892
22 0.01677 0.03354 0.9832
23 0.01779 0.03559 0.9822
24 0.01625 0.0325 0.9838
25 0.02823 0.05647 0.9718
26 0.01988 0.03977 0.9801
27 0.01421 0.02841 0.9858
28 0.008766 0.01753 0.9912
29 0.005845 0.01169 0.9942
30 0.009954 0.01991 0.99
31 0.008223 0.01645 0.9918
32 0.05697 0.1139 0.943
33 0.04511 0.09023 0.9549
34 0.04667 0.09334 0.9533
35 0.04662 0.09324 0.9534
36 0.03427 0.06855 0.9657
37 0.02627 0.05254 0.9737
38 0.01825 0.0365 0.9817
39 0.05413 0.1083 0.9459
40 0.04565 0.0913 0.9544
41 0.044 0.08801 0.956
42 0.03654 0.07308 0.9635
43 0.02854 0.05709 0.9715
44 0.02003 0.04005 0.98
45 0.0139 0.0278 0.9861
46 0.01255 0.02511 0.9874
47 0.008631 0.01726 0.9914
48 0.008793 0.01759 0.9912
49 0.1802 0.3603 0.8198
50 0.4563 0.9126 0.5437
51 0.4417 0.8835 0.5583
52 0.4974 0.9949 0.5026
53 0.4744 0.9489 0.5256
54 0.4459 0.8917 0.5541
55 0.4484 0.8969 0.5516
56 0.4368 0.8737 0.5632
57 0.3828 0.7657 0.6172
58 0.4216 0.8432 0.5784
59 0.4533 0.9066 0.5467
60 0.4148 0.8297 0.5852
61 0.3793 0.7587 0.6207
62 0.3742 0.7484 0.6258
63 0.5406 0.9188 0.4594
64 0.4766 0.9532 0.5234
65 0.4195 0.8389 0.5805
66 0.398 0.796 0.602
67 0.4244 0.8489 0.5756
68 0.3689 0.7378 0.6311
69 0.3471 0.6942 0.6529
70 0.3224 0.6448 0.6776
71 0.2619 0.5238 0.7381
72 0.2144 0.4287 0.7856
73 0.2969 0.5938 0.7031
74 0.355 0.71 0.645
75 0.6256 0.7487 0.3744
76 0.7159 0.5682 0.2841
77 0.6344 0.7312 0.3656
78 0.7238 0.5523 0.2762
79 0.6511 0.6978 0.3489
80 0.5702 0.8596 0.4298
81 0.6279 0.7441 0.3721
82 0.5245 0.951 0.4755
83 0.7124 0.5753 0.2876
84 0.6845 0.6309 0.3155
85 0.6459 0.7082 0.3541
86 0.484 0.9679 0.516


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1 0.01266NOK
5% type I error level240.303797NOK
10% type I error level350.443038NOK


Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted
	RESET test
data:  mylm
RESET = 0.89047, df1 = 2, df2 = 87, p-value = 0.4142
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors
	RESET test
data:  mylm
RESET = 1.6314, df1 = 8, df2 = 81, p-value = 0.1287
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components
	RESET test
data:  mylm
RESET = 0.66387, df1 = 2, df2 = 87, p-value = 0.5174


Variance Inflation Factors (Multicollinearity)
> vif
   KVDD1    KVDD2    KVDD3    KVDD4 
1.052731 1.032114 1.049427 1.045602