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#Exported Settings for TSM Version 4.31.13-05-10 at  9:04:08 on 13-05-2010
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  END_SAMPLE = 300;
  AR_ORDER = 1;
  CORRELOGRAM_ORDER = 1;
  COVMAT_TYPE = 0;
  INPUT_FILE = "TSAEx6.xls";
  IS_ARFIMA = 1;
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839

***********************************************************************
TSM4.25.13-03-08 Run 126 at 10:19:27 on 19-03-2008
Data file is  
C:\Documents\Time Series Analysis\TSM Exercises\TSAEx6.xls
Dependent Variable is Xvariable
200 observations (101-300) used for estimation
with 100 pre-sample observations.
Estimation Method: Conditional ML (Time Domain)
Gaussian Likelihood
ARIMA(1,0,1)
MA form is 1 - a_1 L -...- a_q L^q.
Covariance matrix from robust formula.
Monte Carlo Experiment with 1000 replications:
Frequency Tables with 100 Bins
Data generation model is 'ARMA(1,1)_.5,0,1' (disturbances from model)
Presample data generated randomly.
Data Generation Model Parameters:
AR1                0.50000
MA1                0.00000
Variance            1.0000
Estimated model is 'ARMA(1,1)_.5,0,1'

     ... Run completed in  2:24.48

1
9
Xvariable
2
0

0

3
3
AR1
3
MA1
8
Variance
1
0

0
0
3
449

***********************************************************************
TSM4.31.10-05-10 Run 6 at  8:01:28 on 13-05-2010
Data file is  c:\documents\tsmod4\TSAEx6.xls
Dependent Variable is Xvariable
200 observations  (101-300) used for estimation
with 100 pre-sample observations.
Estimation Method: Conditional ML (Time Domain)
Gaussian Likelihood
ARIMA(1,0,1)
MA form is 1 - a_1 L -...- a_q L^q.
Covariance matrix from information matrix formula.

48

Monte Carlo Experiment with 1000 replications.

373
Random Number Seed = 28888
Frequency Tables with 100 Bins.
Data generation model is 'ARMA(1,1)_.5,0,1' (disturbances from model)
Presample data generated randomly.
Data Generation Model Parameters:
AR1                0.50000
MA1                0.00000
Variance            1.0000
Estimated model is 'ARMA(1,1)_.5,0,1'
     ... 1000 replications completed in 2 min, 33 secs.

10
0
1
0

0

0
0

0
3
6
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6
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TSAEx6.xls
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3
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3
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8
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7
|t|,AR1
7
|t|,MA1
12
|t|,Variance
6
3
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MA1
8
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7
|t|,AR1
7
|t|,MA1
12
|t|,Variance
0
1
837

***********************************************************************
TSM4.25.13-03-08 Run 125 at 10:14:58 on 19-03-2008
Data file is  
C:\Documents\Time Series Analysis\TSM Exercises\TSAEx6.xls
Dependent Variable is Xvariable
200 observations (101-300) used for estimation
with 100 pre-sample observations.
Estimation Method: Conditional ML (Time Domain)
Gaussian Likelihood
ARIMA(1,0,1)
MA form is 1 - a_1 L -...- a_q L^q.
Covariance matrix from robust formula.
Monte Carlo Experiment with 1000 replications:
Frequency Tables with 100 Bins
Data generation model is 'ARMA(1,1)_0,0,1' (disturbances from model)
Presample data generated randomly.
Data Generation Model Parameters:
AR1                0.00000
MA1                0.00000
Variance            1.0000
Estimated model is 'ARMA(1,1)_0,0,1'

     ... Run completed in  2:31.72

1
9
Xvariable
2
0

0

3
3
AR1
3
MA1
8
Variance
1
0

0
0
3
449

***********************************************************************
TSM4.31.10-05-10 Run 5 at  7:56:10 on 13-05-2010
Data file is  c:\documents\tsmod4\TSAEx6.xls
Dependent Variable is Xvariable
200 observations  (101-300) used for estimation
with 100 pre-sample observations.
Estimation Method: Conditional ML (Time Domain)
Gaussian Likelihood
ARIMA(1,0,1)
MA form is 1 - a_1 L -...- a_q L^q.
Covariance matrix from information matrix formula.

48

Monte Carlo Experiment with 1000 replications.

456
Random Number Seed = 28570
Frequency Tables with 100 Bins.
Data generation model is 'ARMA(1,1)_0,0,1' (disturbances from model)
Presample data generated randomly.
Data Generation Model Parameters:
AR1                0.00000
MA1                0.00000
Variance            1.0000
Estimated model is 'ARMA(1,1)_0,0,1'
     ... 1000 replications completed in 2 min, 53 secs.
Convergence failure in 1 replications.
Results based on 999 successful replications.

10
0
1
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0

0
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0
3
6
Actual
6
Fitted
9
Residuals
6
Series
1
3
123
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0

0
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0
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0

0
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0

0
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0
1
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0

0
0

0
6
3
AR1
3
MA1
8
Variance
7
|t|,AR1
7
|t|,MA1
12
|t|,Variance
15
MonteCarlo_Reps
4
1
5
0
1
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0

0
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11
1
 
1
 
10
TSAEx6.xls
16
ARMA(11)_501.tsd
16
ARMA(1,1)_.5,0,1
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  START_SAMPLE = 101;
  END_SAMPLE = 300;
  AR_ORDER = 1;
  CORRELOGRAM_ORDER = 1;
  COVMAT_TYPE = 0;
  INPUT_FILE = "TSAEx6.xls";
  IS_ARFIMA = 1;
  LISTING_FILE = "ARMA(11)_501.tsd";
  MA_ORDER = 1;
  METHOD = GAUSS_ML;
  SERIES = {"Xvariable"};
  RANDOM_PRESAMPLE = 1;
  AR_START_VALUES = {<0.5>};
  VAR_START_VALUES = {<1>};

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AR1
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|t|,Variance
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1
839

***********************************************************************
TSM4.25.13-03-08 Run 126 at 10:19:27 on 19-03-2008
Data file is  
C:\Documents\Time Series Analysis\TSM Exercises\TSAEx6.xls
Dependent Variable is Xvariable
200 observations (101-300) used for estimation
with 100 pre-sample observations.
Estimation Method: Conditional ML (Time Domain)
Gaussian Likelihood
ARIMA(1,0,1)
MA form is 1 - a_1 L -...- a_q L^q.
Covariance matrix from robust formula.
Monte Carlo Experiment with 1000 replications:
Frequency Tables with 100 Bins
Data generation model is 'ARMA(1,1)_.5,0,1' (disturbances from model)
Presample data generated randomly.
Data Generation Model Parameters:
AR1                0.50000
MA1                0.00000
Variance            1.0000
Estimated model is 'ARMA(1,1)_.5,0,1'

     ... Run completed in  2:24.48

1
9
Xvariable
2
0

0

3
3
AR1
3
MA1
8
Variance
1
0

0
0
3
449

***********************************************************************
TSM4.31.10-05-10 Run 6 at  8:01:28 on 13-05-2010
Data file is  c:\documents\tsmod4\TSAEx6.xls
Dependent Variable is Xvariable
200 observations  (101-300) used for estimation
with 100 pre-sample observations.
Estimation Method: Conditional ML (Time Domain)
Gaussian Likelihood
ARIMA(1,0,1)
MA form is 1 - a_1 L -...- a_q L^q.
Covariance matrix from information matrix formula.

48

Monte Carlo Experiment with 1000 replications.

373
Random Number Seed = 28888
Frequency Tables with 100 Bins.
Data generation model is 'ARMA(1,1)_.5,0,1' (disturbances from model)
Presample data generated randomly.
Data Generation Model Parameters:
AR1                0.50000
MA1                0.00000
Variance            1.0000
Estimated model is 'ARMA(1,1)_.5,0,1'
     ... 1000 replications completed in 2 min, 33 secs.

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TSAEx6.xls
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  START_SAMPLE = 101;
  END_SAMPLE = 300;
  AR_ORDER = 1;
  CORRELOGRAM_ORDER = 1;
  COVMAT_TYPE = 0;
  INPUT_FILE = "TSAEx6.xls";
  IS_ARFIMA = 1;
  LISTING_FILE = "ARMA(11)_025.tsd";
  MA_ORDER = 1;
  METHOD = GAUSS_ML;
  SERIES = {"Xvariable"};
  RANDOM_PRESAMPLE = 1;
  MA_START_VALUES = {<2>};
  VAR_START_VALUES = {<0.5>};

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839

***********************************************************************
TSM4.25.13-03-08 Run 127 at 10:24:57 on 19-03-2008
Data file is  
C:\Documents\Time Series Analysis\TSM Exercises\TSAEx6.xls
Dependent Variable is Xvariable
200 observations (101-300) used for estimation
with 100 pre-sample observations.
Estimation Method: Conditional ML (Time Domain)
Gaussian Likelihood
ARIMA(1,0,1)
MA form is 1 - a_1 L -...- a_q L^q.
Covariance matrix from robust formula.
Monte Carlo Experiment with 1000 replications:
Frequency Tables with 100 Bins
Data generation model is 'ARMA(1,1)_0,2,.5' (disturbances from model)
Presample data generated randomly.
Data Generation Model Parameters:
AR1                0.00000
MA1                 2.0000
Variance           0.50000
Estimated model is 'ARMA(1,1)_0,2,.5'

     ... Run completed in  2:24.37

1
9
Xvariable
2
0

0

3
3
AR1
3
MA1
8
Variance
1
0

0
0
3
449

***********************************************************************
TSM4.31.10-05-10 Run 1 at  7:43:57 on 13-05-2010
Data file is  c:\documents\tsmod4\TSAEx6.xls
Dependent Variable is Xvariable
200 observations  (101-300) used for estimation
with 100 pre-sample observations.
Estimation Method: Conditional ML (Time Domain)
Gaussian Likelihood
ARIMA(1,0,1)
MA form is 1 - a_1 L -...- a_q L^q.
Covariance matrix from information matrix formula.

48

Monte Carlo Experiment with 1000 replications.

373
Random Number Seed = 27837
Frequency Tables with 100 Bins.
Data generation model is 'ARMA(1,1)_0,2,.5' (disturbances from model)
Presample data generated randomly.
Data Generation Model Parameters:
AR1                0.00000
MA1                 2.0000
Variance           0.50000
Estimated model is 'ARMA(1,1)_0,2,.5'
     ... 1000 replications completed in 2 min, 37 secs.

10
0
1
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0
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Version: 4.31.13-05-10