Multiple Linear Regression - Estimated Regression Equation
TVDCSUM[t] = -3.06225 + 0.0882605ECSUM[t] -0.0310463EPSUM[t] -0.014804IKSUM[t] -0.00582557KVDDSUM[t] + 0.501122SKEOUSUM[t] + 0.484291GWSUM[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0		2-tail p-value1-tail p-value
(Intercept)-3.062 3.569-8.5790e-01 0.3939 0.1969
ECSUM+0.08826 0.06452+1.3680e+00 0.1757 0.08786
EPSUM-0.03105 0.09878-3.1430e-01 0.7542 0.3771
IKSUM-0.0148 0.09784-1.5130e-01 0.8802 0.4401
KVDDSUM-0.005826 0.08128-7.1670e-02 0.9431 0.4715
SKEOUSUM+0.5011 0.09813+5.1070e+00 2.71e-06 1.355e-06
GWSUM+0.4843 0.1143+4.2370e+00 6.791e-05 3.396e-05


Multiple Linear Regression - Regression Statistics
Multiple R 0.6259
R-squared 0.3918
Adjusted R-squared 0.3397
F-TEST (value) 7.516
F-TEST (DF numerator)6
F-TEST (DF denominator)70
p-value 3.078e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation 1.506
Sum Squared Residuals 158.8


Menu of Residual Diagnostics
DescriptionLink
HistogramCompute
Central TendencyCompute
QQ PlotCompute
Kernel Density PlotCompute
Skewness/Kurtosis TestCompute
Skewness-Kurtosis PlotCompute
Harrell-Davis PlotCompute
Bootstrap Plot -- Central TendencyCompute
Blocked Bootstrap Plot -- Central TendencyCompute
(Partial) Autocorrelation PlotCompute
Spectral AnalysisCompute
Tukey lambda PPCC PlotCompute
Box-Cox Normality PlotCompute
Summary StatisticsCompute


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast		Residuals
Prediction Error
1 13 13.96-0.9589
2 17 16.07 0.9335
3 16 15.88 0.1187
4 17 16.76 0.2425
5 17 14.59 2.41
6 15 16.01-1.013
7 16 16.78-0.778
8 14 15.78-1.784
9 16 15.31 0.6899
10 17 15.04 1.957
11 16 16.36-0.3623
12 16 15.48 0.5209
13 15 15.06-0.06015
14 16 16.57-0.5691
15 13 14.92-1.92
16 15 15.46-0.4619
17 17 17.32-0.3155
18 13 15.13-2.129
19 17 14.6 2.402
20 14 15.14-1.139
21 14 14.27-0.274
22 18 15.46 2.542
23 17 17.1-0.1042
24 13 13.51-0.5118
25 16 17.41-1.407
26 15 16.29-1.285
27 13 14.96-1.956
28 17 16.77 0.2303
29 11 12.56-1.561
30 13 14.44-1.442
31 17 16.46 0.5369
32 16 15.33 0.6735
33 16 16.59-0.5905
34 17 14.6 2.4
35 14 16.03-2.03
36 16 15.46 0.5377
37 15 14.22 0.7758
38 16 15.64 0.3563
39 14 14.7-0.6974
40 15 15.37-0.3702
41 17 15.64 1.359
42 20 16.26 3.745
43 17 15.6 1.397
44 18 17.09 0.913
45 14 12.85 1.153
46 17 16.35 0.6459
47 17 16.15 0.8546
48 16 15.75 0.2454
49 18 13.98 4.024
50 16 16.75-0.7461
51 13 15.68-2.684
52 12 14.68-2.678
53 16 13.7 2.299
54 16 15.64 0.3618
55 16 16.19-0.1918
56 14 15.64-1.639
57 15 14.45 0.5472
58 14 14.54-0.5367
59 15 14.71 0.2897
60 15 15.69-0.6908
61 16 15.22 0.7845
62 11 11.7-0.7048
63 18 15.92 2.075
64 11 14.32-3.317
65 18 18.47-0.4679
66 17 17.17-0.1672
67 14 15.31-1.305
68 17 15.97 1.033
69 14 15.44-1.444
70 19 16.87 2.131
71 16 16.5-0.5011
72 15 15.2-0.2015
73 12 14.18-2.18
74 17 16.78 0.2193
75 15 14.25 0.7525
76 16 15.95 0.05034
77 16 15.03 0.9703


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
10 0.1697 0.3393 0.8303
11 0.07977 0.1595 0.9202
12 0.064 0.128 0.936
13 0.05331 0.1066 0.9467
14 0.05202 0.104 0.948
15 0.1153 0.2306 0.8847
16 0.06746 0.1349 0.9325
17 0.03845 0.0769 0.9616
18 0.1273 0.2546 0.8727
19 0.2128 0.4256 0.7872
20 0.1616 0.3232 0.8384
21 0.1764 0.3528 0.8236
22 0.3268 0.6536 0.6732
23 0.2617 0.5234 0.7383
24 0.2292 0.4585 0.7708
25 0.1946 0.3892 0.8054
26 0.1643 0.3286 0.8357
27 0.1623 0.3246 0.8377
28 0.1183 0.2366 0.8817
29 0.1551 0.3102 0.8449
30 0.1539 0.3077 0.8461
31 0.115 0.23 0.885
32 0.1072 0.2144 0.8928
33 0.08018 0.1604 0.9198
34 0.1351 0.2703 0.8649
35 0.1674 0.3348 0.8326
36 0.1293 0.2586 0.8707
37 0.1087 0.2174 0.8913
38 0.08156 0.1631 0.9184
39 0.07309 0.1462 0.9269
40 0.05444 0.1089 0.9456
41 0.05038 0.1008 0.9496
42 0.3105 0.6209 0.6895
43 0.3561 0.7122 0.6439
44 0.3134 0.6269 0.6866
45 0.3078 0.6155 0.6922
46 0.2684 0.5367 0.7316
47 0.2237 0.4474 0.7763
48 0.1748 0.3496 0.8252
49 0.6283 0.7433 0.3717
50 0.5726 0.8549 0.4274
51 0.6435 0.713 0.3565
52 0.7546 0.4908 0.2454
53 0.8267 0.3466 0.1733
54 0.7914 0.4173 0.2086
55 0.7406 0.5188 0.2594
56 0.726 0.5481 0.274
57 0.6625 0.675 0.3375
58 0.582 0.8361 0.418
59 0.5239 0.9523 0.4761
60 0.4459 0.8919 0.5541
61 0.3802 0.7605 0.6198
62 0.3627 0.7255 0.6373
63 0.4394 0.8789 0.5606
64 0.7702 0.4596 0.2298
65 0.8526 0.2948 0.1474
66 0.8163 0.3673 0.1837
67 0.7173 0.5654 0.2827


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level0 0OK
5% type I error level00OK
10% type I error level10.0172414OK


Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted
	RESET test
data:  mylm
RESET = 0.12967, df1 = 2, df2 = 68, p-value = 0.8786
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors
	RESET test
data:  mylm
RESET = 0.74707, df1 = 12, df2 = 58, p-value = 0.7001
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components
	RESET test
data:  mylm
RESET = 0.76048, df1 = 2, df2 = 68, p-value = 0.4714


Variance Inflation Factors (Multicollinearity)
> vif
   ECSUM    EPSUM    IKSUM  KVDDSUM SKEOUSUM    GWSUM 
1.062707 1.040427 1.070636 1.025101 1.038950 1.017289