Multiple Linear Regression - Estimated Regression Equation
F1C[t] = + 2686.41 + 426.381M1[t] + 366.665M2[t] + 219.948M3[t] -248.435M4[t] -707.985M5[t] -899.535M6[t] -952.418M7[t] -1089.97M8[t] -1096.02M9[t] -798.4M10[t] -609.45M11[t] -4.9502t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0		2-tail p-value1-tail p-value
(Intercept)+2686 109.4+2.4550e+01 1.163e-32 5.815e-33
M1+426.4 134+3.1820e+00 0.002332 0.001166
M2+366.7 133.8+2.7390e+00 0.00813 0.004065
M3+219.9 133.7+1.6450e+00 0.1053 0.05267
M4-248.4 133.6-1.8590e+00 0.06797 0.03398
M5-708 133.5-5.3030e+00 1.792e-06 8.961e-07
M6-899.5 133.4-6.7420e+00 7.397e-09 3.698e-09
M7-952.4 133.4-7.1420e+00 1.556e-09 7.782e-10
M8-1090 133.3-8.1770e+00 2.75e-11 1.375e-11
M9-1096 133.2-8.2250e+00 2.28e-11 1.14e-11
M10-798.4 133.2-5.9930e+00 1.328e-07 6.639e-08
M11-609.5 133.2-4.5750e+00 2.494e-05 1.247e-05
t-4.95 1.327-3.7310e+00 0.0004301 0.000215


Multiple Linear Regression - Regression Statistics
Multiple R 0.9387
R-squared 0.8811
Adjusted R-squared 0.8569
F-TEST (value) 36.43
F-TEST (DF numerator)12
F-TEST (DF denominator)59
p-value 0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation 230.7
Sum Squared Residuals 3.14e+06


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 3035 3108-72.84
2 2552 3043-491.2
3 2704 2892-187.5
4 2554 2418 135.8
5 2014 1954 60.33
6 1655 1757-102.2
7 1721 1699 21.66
8 1524 1557-32.84
9 1596 1546 50.16
10 2074 1839 235.5
11 2199 2023 176.5
12 2512 2627-115
13 2933 3048-115.4
14 2889 2984-94.77
15 2938 2832 105.9
16 2497 2359 138.2
17 1870 1894-24.27
18 1726 1698 28.23
19 1607 1640-32.94
20 1545 1497 47.56
21 1396 1486-90.44
22 1787 1779 7.896
23 2076 1963 112.9
24 2837 2568 269.4
25 2787 2989-202
26 3891 2924 966.6
27 3179 2773 406.3
28 2011 2299-288.4
29 1636 1835-198.9
30 1580 1638-58.37
31 1489 1581-91.53
32 1300 1438-138
33 1356 1427-71.03
34 1653 1720-66.7
35 2013 1904 109.3
36 2823 2508 314.8
37 3102 2930 172.4
38 2294 2865-571
39 2385 2713-328.3
40 2444 2240 204
41 1748 1775-27.47
42 1554 1579-24.97
43 1498 1521-23.13
44 1361 1379-17.63
45 1346 1368-21.63
46 1564 1660-96.3
47 1640 1844-204.3
48 2293 2449-155.8
49 2815 2870-55.23
50 3137 2806 331.4
51 2679 2654 25.1
52 1969 2181-211.6
53 1870 1716 153.9
54 1633 1520 113.4
55 1529 1462 67.27
56 1366 1319 46.77
57 1357 1308 48.77
58 1570 1601-30.9
59 1535 1785-249.9
60 2491 2389 101.6
61 3084 2811 273.2
62 2605 2746-141.2
63 2573 2594-21.49
64 2143 2121 21.84
65 1693 1657 36.34
66 1504 1460 43.84
67 1461 1402 58.67
68 1354 1260 94.17
69 1333 1249 84.17
70 1492 1541-49.49
71 1781 1725 55.51
72 1915 2330-415


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
16 0.2445 0.4889 0.7555
17 0.1877 0.3754 0.8123
18 0.09442 0.1888 0.9056
19 0.05862 0.1172 0.9414
20 0.02661 0.05322 0.9734
21 0.02177 0.04354 0.9782
22 0.02335 0.04669 0.9767
23 0.01233 0.02465 0.9877
24 0.02016 0.04032 0.9798
25 0.01655 0.03309 0.9835
26 0.9348 0.1304 0.06519
27 0.9609 0.07812 0.03906
28 0.9851 0.02984 0.01492
29 0.9855 0.02897 0.01448
30 0.9773 0.04538 0.02269
31 0.9674 0.06514 0.03257
32 0.9583 0.0833 0.04165
33 0.9397 0.1206 0.06029
34 0.9197 0.1605 0.08025
35 0.9053 0.1894 0.09472
36 0.9532 0.09368 0.04684
37 0.9385 0.123 0.06149
38 0.9961 0.007883 0.003942
39 0.9976 0.004793 0.002397
40 0.9984 0.003253 0.001626
41 0.9969 0.006273 0.003137
42 0.994 0.01192 0.005961
43 0.9889 0.02215 0.01108
44 0.9804 0.03926 0.01963
45 0.9668 0.06644 0.03322
46 0.9463 0.1074 0.0537
47 0.9284 0.1432 0.07161
48 0.8939 0.2121 0.1061
49 0.9051 0.1899 0.09493
50 0.9524 0.0953 0.04765
51 0.9135 0.173 0.08652
52 0.9031 0.1938 0.0969
53 0.8399 0.3202 0.1601
54 0.7387 0.5226 0.2613
55 0.5968 0.8065 0.4032
56 0.4328 0.8655 0.5673


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level4 0.09756NOK
5% type I error level150.365854NOK
10% type I error level220.536585NOK


Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted
	RESET test
data:  mylm
RESET = 3.1321, df1 = 2, df2 = 57, p-value = 0.05122
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors
	RESET test
data:  mylm
RESET = 0.035537, df1 = 24, df2 = 35, p-value = 1
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components
	RESET test
data:  mylm
RESET = 0.69464, df1 = 2, df2 = 57, p-value = 0.5034


Variance Inflation Factors (Multicollinearity)
> vif
      M1       M2       M3       M4       M5       M6       M7       M8 
1.855341 1.851521 1.848065 1.844974 1.842245 1.839881 1.837880 1.836243 
      M9      M10      M11        t 
1.834970 1.834061 1.833515 1.028373