Multiple Linear Regression - Estimated Regression Equation
ITH[t] = + 15.2204 + 0.289512K1[t] + 0.0834883K2[t] + 0.191869K3[t] -0.203099K4[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
VariableParameterS.D.T-STAT
H0: parameter = 0		2-tail p-value1-tail p-value
(Intercept)+15.22 1.458+1.0440e+01 2.977e-19 1.489e-19
K1+0.2895 0.2889+1.0020e+00 0.318 0.159
K2+0.08349 0.2224+3.7540e-01 0.7079 0.354
K3+0.1919 0.2187+8.7750e-01 0.3817 0.1909
K4-0.2031 0.2391-8.4940e-01 0.3971 0.1985


Multiple Linear Regression - Regression Statistics
Multiple R 0.1325
R-squared 0.01756
Adjusted R-squared-0.01031
F-TEST (value) 0.6301
F-TEST (DF numerator)4
F-TEST (DF denominator)141
p-value 0.6418
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation 2.437
Sum Squared Residuals 837.5


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast		Residuals
Prediction Error
1 14 16.96-2.957
2 17 16.8 0.2017
3 17 16.6 0.4048
4 15 17.16-2.16
5 20 17.08 2.923
6 15 16.78-1.776
7 19 16.57 2.427
8 15 16.41-1.406
9 15 16.32-1.323
10 19 16.88 2.118
11 20 17.15 2.851
12 18 16.84 1.163
13 15 16.48-1.476
14 14 16.71-2.707
15 20 16.78 3.216
16 16 16.67-0.6704
17 19 15.73 3.267
18 19 16.4 2.597
19 16 16.12-0.1168
20 18 17.17 0.8287
21 17 16.48 0.5244
22 19 17.2 1.804
23 17 16.79 0.2129
24 19 16.67 2.333
25 20 16.48 3.524
26 5 16.58-11.58
27 19 16.77 2.235
28 16 16.77-0.7651
29 15 16.56-1.562
30 16 16.77-0.7651
31 18 15.62 2.379
32 16 16.98-0.979
33 15 16.48-1.476
34 17 15.92 1.075
35 20 16.98 3.021
36 19 16.56 2.438
37 7 16.2-9.2
38 13 16.51-3.512
39 16 17.07-1.065
40 16 16.87-0.8735
41 18 16.4 1.597
42 18 16.58 1.416
43 16 16.68-0.6816
44 17 16.68 0.3184
45 19 16.49 2.51
46 16 16.36-0.356
47 19 16.57 2.427
48 13 16.27-3.272
49 12 16.79-4.788
50 17 16.33 0.666
51 17 16.48 0.5244
52 16 16.49-0.4898
53 16 16.19-0.1861
54 14 16.21-2.211
55 16 16.56-0.562
56 13 16.95-3.954
57 16 16.67-0.6675
58 14 16.77-2.765
59 20 16.96 3.043
60 13 16.77-3.765
61 18 16.31 1.691
62 14 16.86-2.859
63 19 16.12 2.883
64 18 17.04 0.9595
65 14 16.76-2.762
66 18 16.51 1.488
67 19 16.88 2.118
68 15 16.99-1.99
69 14 16.99-2.99
70 19 16.86 2.141
71 13 16.48-3.476
72 19 16.87 2.127
73 18 16.39 1.608
74 20 17.15 2.851
75 15 16.67-1.667
76 15 16.5-1.5
77 15 16.7-1.701
78 20 16.79 3.213
79 15 16.03-1.027
80 19 16.68 2.321
81 18 16.96 1.043
82 18 15.98 2.017
83 15 16.48-1.476
84 20 17.03 2.971
85 17 16.1 0.9003
86 12 16.09-4.095
87 18 16.77 1.235
88 19 16.75 2.246
89 20 16.52 3.477
90 17 16.87 0.1265
91 15 16.67-1.67
92 16 16.67-0.6675
93 18 16.46 1.536
94 14 16.75-2.754
95 15 16.68-1.682
96 12 16.39-4.392
97 17 16.68 0.3184
98 18 16.87 1.127
99 17 16.12 0.8832
100 17 16.95 0.05425
101 20 16.45 3.546
102 16 16 0.002852
103 14 16.2-2.2
104 15 16.39-1.392
105 18 16.6 1.402
106 20 16.67 3.33
107 17 16.58 0.416
108 17 16.77 0.2349
109 17 16.96 0.04302
110 15 16.99-1.99
111 17 16.48 0.5244
112 18 16.63 1.369
113 17 16.94 0.05717
114 20 17.16 2.84
115 15 16.48-1.479
116 16 16.97-0.9653
117 18 16.6 1.405
118 15 16.39-1.389
119 18 16.28 1.716
120 20 16.67 3.33
121 19 16.7 2.296
122 14 17.07-3.074
123 16 16.86-0.8623
124 15 15.91-0.9107
125 17 16.28 0.7163
126 18 15.85 2.154
127 20 16.48 3.521
128 17 16.49 0.5132
129 18 17.16 0.8399
130 15 16.11-1.114
131 16 16.48-0.4756
132 15 16.39-1.392
133 18 16.31 1.691
134 17 16.96 0.04302
135 16 16.41-0.4063
136 12 16.86-4.862
137 19 17.16 1.84
138 15 16.98-1.982
139 17 16.57 0.4268
140 19 16.21 2.786
141 18 16.66 1.335
142 19 16.67 2.333
143 16 16.8-0.7983
144 16 16.95-0.9458
145 16 16.48-0.4756
146 14 16.6-2.595


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
8 0.8243 0.3514 0.1757
9 0.7276 0.5448 0.2724
10 0.6298 0.7405 0.3702
11 0.6544 0.6911 0.3456
12 0.5425 0.9151 0.4575
13 0.5109 0.9782 0.4891
14 0.469 0.9379 0.531
15 0.411 0.8221 0.589
16 0.3214 0.6428 0.6786
17 0.3126 0.6252 0.6874
18 0.2868 0.5737 0.7132
19 0.2241 0.4482 0.7759
20 0.1775 0.3551 0.8225
21 0.1351 0.2701 0.8649
22 0.1233 0.2465 0.8767
23 0.09664 0.1933 0.9034
24 0.07535 0.1507 0.9246
25 0.08197 0.1639 0.918
26 0.9919 0.01621 0.008105
27 0.9908 0.01848 0.00924
28 0.9867 0.02669 0.01335
29 0.9821 0.03578 0.01789
30 0.9749 0.05011 0.02505
31 0.9682 0.06366 0.03183
32 0.9581 0.08376 0.04188
33 0.9519 0.09624 0.04812
34 0.9371 0.1258 0.0629
35 0.9338 0.1323 0.06617
36 0.937 0.126 0.06301
37 0.9994 0.00124 0.0006201
38 0.9996 0.0008581 0.0004291
39 0.9993 0.001302 0.0006509
40 0.999 0.001973 0.0009864
41 0.9987 0.002684 0.001342
42 0.9983 0.003498 0.001749
43 0.9974 0.005165 0.002583
44 0.9963 0.007447 0.003724
45 0.9964 0.007236 0.003618
46 0.9948 0.01031 0.005154
47 0.9946 0.01082 0.00541
48 0.9957 0.008526 0.004263
49 0.9988 0.002351 0.001175
50 0.9983 0.003326 0.001663
51 0.9976 0.004879 0.002439
52 0.9965 0.007045 0.003522
53 0.995 0.01005 0.005026
54 0.9946 0.01078 0.005389
55 0.9925 0.01506 0.00753
56 0.9957 0.008541 0.004271
57 0.994 0.01193 0.005965
58 0.9944 0.01119 0.005596
59 0.9955 0.008924 0.004462
60 0.9972 0.00553 0.002765
61 0.9967 0.00668 0.00334
62 0.997 0.005976 0.002988
63 0.9974 0.005229 0.002614
64 0.9965 0.007057 0.003528
65 0.9969 0.00621 0.003105
66 0.9961 0.007816 0.003908
67 0.9957 0.008638 0.004319
68 0.9952 0.009665 0.004832
69 0.9961 0.007812 0.003906
70 0.9958 0.008344 0.004172
71 0.9973 0.005429 0.002715
72 0.9971 0.005885 0.002942
73 0.9964 0.007251 0.003626
74 0.9968 0.006318 0.003159
75 0.9963 0.007479 0.003739
76 0.9954 0.009207 0.004604
77 0.9947 0.01064 0.005318
78 0.9959 0.008199 0.004099
79 0.9946 0.01082 0.005412
80 0.9944 0.0112 0.005602
81 0.9925 0.01495 0.007475
82 0.9916 0.01689 0.008445
83 0.9898 0.02049 0.01025
84 0.9915 0.01707 0.008537
85 0.9885 0.02296 0.01148
86 0.9954 0.009245 0.004622
87 0.9938 0.01233 0.006166
88 0.9937 0.01264 0.00632
89 0.9956 0.008742 0.004371
90 0.9937 0.0127 0.006348
91 0.9927 0.01463 0.007316
92 0.9898 0.02031 0.01016
93 0.9875 0.02508 0.01254
94 0.9898 0.0205 0.01025
95 0.9886 0.0228 0.0114
96 0.9966 0.006775 0.003387
97 0.995 0.01008 0.005038
98 0.9931 0.01385 0.006925
99 0.9901 0.01974 0.009868
100 0.9859 0.02828 0.01414
101 0.9902 0.01958 0.009789
102 0.9862 0.02766 0.01383
103 0.988 0.024 0.012
104 0.9864 0.02728 0.01364
105 0.9816 0.03677 0.01839
106 0.9864 0.02728 0.01364
107 0.9803 0.03931 0.01965
108 0.972 0.05594 0.02797
109 0.9609 0.07823 0.03911
110 0.9567 0.08657 0.04328
111 0.9411 0.1179 0.05894
112 0.9247 0.1505 0.07527
113 0.9003 0.1994 0.09968
114 0.9252 0.1496 0.07478
115 0.9187 0.1626 0.0813
116 0.8922 0.2156 0.1078
117 0.8708 0.2584 0.1292
118 0.8507 0.2986 0.1493
119 0.8197 0.3607 0.1803
120 0.8602 0.2796 0.1398
121 0.8713 0.2574 0.1287
122 0.8806 0.2388 0.1194
123 0.8408 0.3183 0.1592
124 0.8237 0.3525 0.1763
125 0.7687 0.4625 0.2313
126 0.7313 0.5374 0.2687
127 0.8097 0.3806 0.1903
128 0.7464 0.5073 0.2536
129 0.7005 0.5991 0.2995
130 0.6821 0.6359 0.3179
131 0.6064 0.7872 0.3936
132 0.5753 0.8495 0.4247
133 0.495 0.9899 0.505
134 0.4007 0.8014 0.5993
135 0.2939 0.5877 0.7061
136 0.5295 0.9411 0.4705
137 0.7145 0.5709 0.2855
138 0.5532 0.8935 0.4468


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level37 0.2824NOK
5% type I error level750.572519NOK
10% type I error level820.625954NOK


Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted
	RESET test
data:  mylm
RESET = 1.6834, df1 = 2, df2 = 139, p-value = 0.1895
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors
	RESET test
data:  mylm
RESET = 1.0815, df1 = 8, df2 = 133, p-value = 0.38
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components
	RESET test
data:  mylm
RESET = 1.196, df1 = 2, df2 = 139, p-value = 0.3055


Variance Inflation Factors (Multicollinearity)
> vif
      K1       K2       K3       K4 
1.145132 1.046995 1.063335 1.136731