Regression Forecasting

  • June 2020
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Input No. of Variables No. of Observations Dependent 94.20 46.26 33.67 69.79 58.00 22.91 79.94 24.33 5.72 53.25 44.33 46.00 24.49 38.83 19.80 21.17 22.00 23.00 39.83 64.21

Indep1 103.63 52.06 43.12 70.95 67.98 28.23 89.26 31.88 9.15 56.30 51.74 51.41 33.98 43.20 25.22 28.18 28.72 27.74 40.47 67.30

Indep2 60.14 10.93 18.97 47.55 30.07 17.13 59.46 -0.88 -27.06 44.46 21.47 19.79 -2.75 2.04 -16.86 12.33 -17.54 -11.43 36.39 49.12

Indep3 45.08 7.14 40.19 40.57 42.06 85.04 97.38 54.63 20.33 77.93 12.79 14.35 95.47 58.81 4.07 7.43 19.94 20.19 70.21 49.64

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Input

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Input

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Input 4 20

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Input

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Input

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Input 0

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Input

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Input

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Input

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Input

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Input

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Input

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Input

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Input

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Input

20

10

0.91

Actual Predicted Residual e^2 (e-et-1)^2 94.2 94.86 0.65 46.26 45.41 -0.85 0.72 2.26 33.67 38.05 4.37 19.14 27.3 69.79 65.42 -4.37 19.13 76.54 58 60.66 2.66 7.1 49.55 22.91 24.09 1.18 1.4 2.2 79.94 81.34 1.41 1.98 0.05 24.33 25.63 1.3 1.69 0.01 5.72 3.66 -2.06 4.24 11.29 53.25 51.69 -1.57 2.46 0.24 44.33 46.33 2 3.99 12.71 46 45.8 -0.2 0.04 4.83 24.49 26.31 1.82 3.32 4.09 38.83 35.6 -3.23 10.45 25.56 19.8 19.04 -0.76 0.58 6.12 21.17 25.14 3.97 15.79 22.39 22 21.61 -0.39 0.16 19.07 23 21.52 -1.48 2.18 1.18 39.83 37.29 -2.54 6.44 1.12 64.21 62.29 -1.92 3.7 0.38

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2.55 d 1 dl 1.68 du

0 Positive Autocorrelation dete 1 Positive Autocorrelation may 1.68 No Autocorrelation detected 2.32 Negative Autocorrelation ma 3 Negative Autocorrelation de 4 Negative Autocorrelation de

4 Negative Autocorrelation ma

Input

104.51

266.9

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Input

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Input

Positive Autocorrelation detected Positive Autocorrelation maybe present No Autocorrelation detected Negative Autocorrelation maybe present Negative Autocorrelation detected Negative Autocorrelation detected

Negative Autocorrelation maybe present

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Input

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Output

Equation Parameters

Intercept Indep1 Indep2 Indep3

Independent Analysis

Coefficients

Standard Error

-0.357 0.856 0.125 -0.022

2.290 0.055 0.053 0.022

=

R Squared

98.57% 81.60% 7.59%

Gradient

Dl=1.20 Du=1.41

Intercept

0.97 0.79 0.21

Auto Correlation

-4.60 27.66 32.57

Tests for Multicolinearity between Independent Variables

DW-Stat

Adjusted RSquared against other Indep

2.43 1.90 1.71

76.97% 79.68% 14.43%

0.86*Indep1 + 0.12*Indep2 + -0.02*Indep3 + -0.36 (+/- 2.56)

Independent R-Square Matrix 100%

78%

8%

Indep1

78%

100%

19%

Indep2

8%

19%

100%

Indep3

Actual versus Predicted Trend R-Squared Matrix

100

f(x) = 0.99x + 0.44 R² = 0.99

90 80

Predicted

Step 2 - Forecasting

Independent Variable Indep1 Indep2 Indep3

70 60

Linear

Multiple Regression Equation

Exponential

498.8907

2nd Ord Polynomial

2.5609

F - Statistic

3rd Ord Polynomial

Standard Error

98.94% of the change in can be explained by the change in the 3 Independent Variables Adjusted for Sample Size bias 2.55384 Durbin-Watson Statistic Critical D-W Values: Lower (Dl)=1.00; Upper (Du)=1.68 to +/- on result of Regression Equation Therefore Negative Autocorrelation maybe present at 95% Confidence Therefore analysis IS Significant 3.12735 Critical F-Statistic at 95% Confidence (Significance holds to 100.0% Level of Confidence)

Indep3

0.9874

Indep2

0.9894

Adjusted R Square

Indep1

R Square

33% 31% 18%

33% 22% 3%

11% ### 2%

20% 10% 1%

50 40 30 20 10 10

20

30

40

50

Actual

60

70

80

90

100 Number of Periods to Forecast

10

Choose Method Linear Linear Linear

-0.36 Time Period

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

Forecast Output 0.86

Indep1

103.63 52.06 43.12 70.95 67.98 28.23 89.26 31.88 9.15 56.30 51.74 51.41 33.98 43.20 25.22 28.18 28.72 27.74 40.47 67.30 29.20 27.45 25.71 23.96 22.22 20.47 18.72 16.98 15.23 13.49 11.74

0.12

Indep2

60.14 10.93 18.97 47.55 30.07 17.13 59.46 -0.88 -27.06 44.46 21.47 19.79 -2.75 2.04 -16.86 12.33 -17.54 -11.43 36.39 49.12 2.88 1.47 0.06 -1.35 -2.75 -4.16 -5.57 -6.98 -8.39 -9.80 -11.21

-0.02 Indep3

45.08 7.14 40.19 40.57 42.06 85.04 97.38 54.63 20.33 77.93 12.79 14.35 95.47 58.81 4.07 7.43 19.94 20.19 70.21 49.64

Dependent

94.20 46.26 33.67 69.79 58.00 22.91 79.94 24.33 5.72 53.25 44.33 46.00 24.49 38.83 19.80 21.17 22.00 23.00 39.83 64.21 24.99 23.32 21.65 19.98 18.31 16.64 14.97 13.30 11.63 9.97 8.30

Time Period

37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74

Indep1

Indep2

Indep3

Dependent

Time Period

75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112

Indep1

Indep2

Indep3

Dependent

Time Period

113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150

Indep1

Indep2

Indep3

Dependent

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