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Regression Results for (ConsGOODS)

⇐ ПредыдущаяСтр 3 из 4Следующая ⇒


  Fitted Stnd. Error Lower 95, 0% Upper 95, 0%
Row Value CL for Forecast CL for Forecast CL for Forecast
1151, 87 164, 741 824, 531 1479, 21
1154, 85 164, 747 827, 501 1482, 2
1157, 84 164, 753 830, 479 1485, 2
1160, 84 164, 759 833, 464 1488, 21
1163, 84 164, 764 836, 457 1491, 23
1166, 85 164, 77 839, 458 1494, 25

 

 

4) N=80

 

Multiple Regression - (ConsGOODS) (num> 44)

Dependent variable: (ConsGOODS)

Independent variables:

1.09^(0.03*num)

Selection variable: num> 44

 

    Standard T  
Parameter Estimate Error Statistic P-Value
1.09^(0.03*num) 841, 442 15, 2694 55, 1066 0, 0000

 

Analysis of Variance

Source Sum of Squares Df Mean Square F-Ratio P-Value
Model 8, 83044E7 8, 83044E7 3036, 74 0, 0000
Residual 2, 29722E6 29078, 7    
Total 9, 06016E7      

 

R-squared = 97, 4645 percent

R-squared (adjusted for d.f.) = 97, 4645 percent

Standard Error of Est. = 170, 525

Mean absolute error = 134, 175

Durbin-Watson statistic = 0, 0912601

Lag 1 residual autocorrelation = 0, 948629

 

 

(ConsGOODS) = 841, 442*1.09^(0.03*num)

 

Regression Results for (ConsGOODS)

  Fitted Stnd. Error Lower 95, 0% Upper 95, 0%
Row Value CL for Forecast CL for Forecast CL for Forecast
1162, 45 171, 825 820, 439 1504, 46
1165, 46 171, 831 823, 435 1507, 48
1168, 47 171, 838 826, 439 1510, 51
1171, 5 171, 845 829, 45 1513, 55
1174, 53 171, 852 832, 469 1516, 59
1177, 57 171, 858 835, 496 1519, 65

 

 

5) N=60

 

Multiple Regression - (ConsGOODS) (num> 64)

Dependent variable: (ConsGOODS)

Independent variables:

1.09^(0.03*num)

Selection variable: num> 64

 

    Standard T  
Parameter Estimate Error Statistic P-Value
1.09^(0.03*num) 852, 086 18, 9632 44, 9337 0, 0000

 

Analysis of Variance

Source Sum of Squares Df Mean Square F-Ratio P-Value
Model 7, 12962E7 7, 12962E7 2019, 04 0, 0000
Residual 2, 08341E6 35312, 0    
Total 7, 33796E7      

 

R-squared = 97, 1608 percent

R-squared (adjusted for d.f.) = 97, 1608 percent

Standard Error of Est. = 187, 915

Mean absolute error = 146, 082

Durbin-Watson statistic = 0, 0880797

Lag 1 residual autocorrelation = 0, 9533

 

 

(ConsGOODS) = 852, 086*1.09^(0.03*num)

 

Regression Results for (ConsGOODS)

  Fitted Stnd. Error Lower 95, 0% Upper 95, 0%
Row Value CL for Forecast CL for Forecast CL for Forecast
1177, 15 189, 732 797, 499 1556, 81
1180, 2 189, 742 800, 528 1559, 87
1183, 26 189, 751 803, 564 1562, 95
1186, 32 189, 76 806, 608 1566, 03
1189, 39 189, 77 809, 66 1569, 12
1192, 47 189, 78 812, 72 1572, 22

 

6) N=40

 

Multiple Regression - (ConsGOODS) (num> 84)

Dependent variable: (ConsGOODS)

Independent variables:

1.09^(0.03*num)

Selection variable: num> 84

 

    Standard T  
Parameter Estimate Error Statistic P-Value
1.09^(0.03*num) 790, 103 19, 7345 40, 0366 0, 0000

 

Analysis of Variance

Source Sum of Squares Df Mean Square F-Ratio P-Value
Model 4, 29402E7 4, 29402E7 1602, 93 0, 0000
Residual 1, 04475E6 26788, 5    
Total 4, 3985E7      

 

R-squared = 97, 6248 percent

R-squared (adjusted for d.f.) = 97, 6248 percent

Standard Error of Est. = 163, 672

Mean absolute error = 133, 988

Durbin-Watson statistic = 0, 141224

Lag 1 residual autocorrelation = 0, 863244

 

 

(ConsGOODS) = 790, 103*1.09^(0.03*num)

 

Regression Results for (ConsGOODS)

  Fitted Stnd. Error Lower 95, 0% Upper 95, 0%
Row Value CL for Forecast CL for Forecast CL for Forecast
1091, 52 165, 927 755, 903 1427, 14
1094, 35 165, 939 758, 705 1429, 99
1097, 18 165, 95 761, 514 1432, 85
1100, 02 165, 962 764, 331 1435, 71
1102, 87 165, 974 767, 155 1438, 58
1105, 72 165, 986 769, 986 1441, 46

 

7) N=30

 

Multiple Regression - (ConsGOODS) (num> 94)

Dependent variable: (ConsGOODS)

Independent variables:

1.09^(0.03*num)

Selection variable: num> 94

 

    Standard T  
Parameter Estimate Error Statistic P-Value
1.09^(0.03*num) 761, 061 21, 3113 35, 7116 0, 0000

 

Analysis of Variance

Source Sum of Squares Df Mean Square F-Ratio P-Value
Model 3, 06399E7 3, 06399E7 1275, 32 0, 0000
Residual 696733, 24025, 3    
Total 3, 13366E7      

 

R-squared = 97, 7766 percent

R-squared (adjusted for d.f.) = 97, 7766 percent

Standard Error of Est. = 155, 001

Mean absolute error = 137, 699

Durbin-Watson statistic = 0, 109184

Lag 1 residual autocorrelation = 0, 928375

 

 

(ConsGOODS) = 761, 061*1.09^(0.03*num)

 

Regression Results for (ConsGOODS)

  Fitted Stnd. Error Lower 95, 0% Upper 95, 0%
Row Value CL for Forecast CL for Forecast CL for Forecast
1051, 4 157, 772 728, 721 1374, 08
1054, 12 157, 786 731, 414 1376, 83
1056, 85 157, 801 734, 113 1379, 59
1059, 59 157, 815 736, 82 1382, 36
1062, 33 157, 83 739, 533 1385, 13
1065, 08 157, 844 742, 253 1387, 91

 

8) N=20

 

Multiple Regression - (ConsGOODS) (num> 104)

Dependent variable: (ConsGOODS)

Independent variables:

1.09^(0.03*num)

Selection variable: num> 104

 

    Standard T  
Parameter Estimate Error Statistic P-Value
1.09^(0.03*num) 830, 343 12, 2457 67, 8068 0, 0000

 

Analysis of Variance

Source Sum of Squares Df Mean Square F-Ratio P-Value
Model 2, 49378E7 2, 49378E7 4597, 77 0, 0000
Residual 103054, 5423, 89    
Total 2, 50408E7      

 

R-squared = 99, 58 percent

R-squared (adjusted for d.f.) = 99, 5885 percent

Standard Error of Est. = 73, 647

Mean absolute error = 52, 5364

Durbin-Watson statistic = 0, 293051

Lag 1 residual autocorrelation = 0, 6808

 

 

(ConsGOODS) = 830, 343*1.09^(0.03*num)

Regression Results for (ConsGOODS)

  Fitted Stnd. Error Lower 95, 0% Upper 95, 0%
Row Value CL for Forecast CL for Forecast CL for Forecast
1147, 11 75, 5651 988, 954 1305, 27
1150, 08 75, 5749 991, 903 1308, 26
1153, 06 75, 5848 994, 86 1311, 26
1156, 05 75, 5947 997, 824 1314, 27
1159, 04 75, 6047 1000, 8 1317, 28
1162, 04 75, 6147 1003, 78 1320, 3

 

9) Таблица для расчета прогностических характеристик в зависимости от длины ретроспективного периода

тестовая выборка значение показателя n (n< =T)
1156, 66 1149, 52 1147, 32 1144, 09 1151, 87 1162, 45 1177, 2 1091, 52 1051, 4 1147, 11
1155, 66 1152, 49 1150, 29 1147, 05 1154, 85 1165, 46 1180, 2 1094, 35 1054, 12 1150, 08
1134, 28 1155, 48 1153, 27 1150, 02 1157, 84 1168, 47 1183, 3 1097, 18 1056, 85 1153, 06
1104, 87 1158, 47 1156, 25 1160, 84 1171, 5 1186, 3 1100, 02 1059, 59 1156, 05
1055, 55 1161, 47 1159, 24 1155, 98 1163, 84 1174, 53 1189, 4 1102, 87 1062, 33 1159, 04

 

Приложение 11

Анализ автокорреляции ряда

Estimated Autocorrelations for ConsGOODS

 

      Lower 95, 0% Upper 95, 0%
Lag Autocorrelation Stnd. Error Prob. Limit Prob. Limit
0, 955248 0, 0883883 -0, 173238 0, 173238
0, 904005 0, 148561 -0, 291174 0, 291174
0, 853554 0, 186653 -0, 365834 0, 365834
0, 799529 0, 214996 -0, 421384 0, 421384
0, 736516 0, 237089 -0, 464687 0, 464687
0, 663977 0, 254337 -0, 498492 0, 498492
0, 596651 0, 267536 -0, 524363 0, 524363
0, 534354 0, 277737 -0, 544357 0, 544357
0, 463317 0, 285656 -0, 559877 0, 559877
0, 38415 0, 291468 -0, 571268 0, 571268
0, 312689 0, 295397 -0, 578969 0, 578969
0, 242585 0, 297972 -0, 584015 0, 584015
0, 167343 0, 299511 -0, 587031 0, 587031
0, 10929 0, 30024 -0, 588461 0, 588461
0, 0592736 0, 300551 -0, 58907 0, 58907
0, 0189565 0, 300642 -0, 589249 0, 589249
-0, 0183854 0, 300652 -0, 589267 0, 589267
-0, 0457655 0, 30066 -0, 589285 0, 589285
-0, 0616535 0, 300715 -0, 589391 0, 589391
-0, 0831201 0, 300814 -0, 589585 0, 589585
-0, 0981423 0, 300993 -0, 589936 0, 589936
-0, 114109 0, 301243 -0, 590426 0, 590426
-0, 11543 0, 30158 -0, 591088 0, 591088
-0, 112791 0, 301925 -0, 591764 0, 591764

 

Estimated Partial Autocorrelations for ConsGOODS

 

  Partial   Lower 95, 0% Upper 95, 0%
Lag Autocorrelation Stnd. Error Prob. Limit Prob. Limit
0, 955248 0, 0883883 -0, 173238 0, 173238
-0, 0970735 0, 0883883 -0, 173238 0, 173238
-0, 0126156 0, 0883883 -0, 173238 0, 173238
-0, 0701198 0, 0883883 -0, 173238 0, 173238
-0, 128263 0, 0883883 -0, 173238 0, 173238
-0, 136785 0, 0883883 -0, 173238 0, 173238
0, 027253 0, 0883883 -0, 173238 0, 173238
0, 0123685 0, 0883883 -0, 173238 0, 173238
-0, 13413 0, 0883883 -0, 173238 0, 173238
-0, 121182 0, 0883883 -0, 173238 0, 173238
0, 037319 0, 0883883 -0, 173238 0, 173238
-0, 0683891 0, 0883883 -0, 173238 0, 173238
-0, 108885 0, 0883883 -0, 173238 0, 173238
0, 192417 0, 0883883 -0, 173238 0, 173238
0, 0172174 0, 0883883 -0, 173238 0, 173238
0, 0230192 0, 0883883 -0, 173238 0, 173238
-0, 00320551 0, 0883883 -0, 173238 0, 173238
0, 0899016 0, 0883883 -0, 173238 0, 173238
0, 0124698 0, 0883883 -0, 173238 0, 173238
-0, 1466 0, 0883883 -0, 173238 0, 173238
0, 0986533 0, 0883883 -0, 173238 0, 173238
-0, 0968146 0, 0883883 -0, 173238 0, 173238
0, 0642445 0, 0883883 -0, 173238 0, 173238
0, 0192838 0, 0883883 -0, 173238 0, 173238

 


Приложение 12

Расчет Q-статистики Бокса-Пирса и Бокса-Льюинга


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