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SmartData Collective > Uncategorized > Learn Time Series Analysis: Free Materials for SAS Users
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Learn Time Series Analysis: Free Materials for SAS Users

JiangtangHu
Last updated: 2009/02/05 at 8:12 AM
JiangtangHu
4 Min Read
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0. A gentle Introduction to Time Series Analysis, may serve as fast learning materials:

http://www.itl.nist.gov/div898/handbook/pmc/section4/pmc4.htm

1. An open source book(with data and code), A First Course on Time Series Analysis: examples with SAS, by Prof. Michael Falk, is available in:

http://statistik.mathematik.uni-wuerzburg.de/timeseries/

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2. A SAS User book, Forecasting Examples for Business and Economics Using SAS by B. Cohen (another popular SAS User book for time series is SAS for Forecasting Time Series by John Brocklebank and David Dickey), is example-driven approach. You can review and submit the codes to learn SAS for time series analysis in a comprehensive way–there are 30 examples available:

1. Forecasting an Autoregressive Progress
2. Forecasting a Moving Average Process
3. Forecasting a Seasonal Process
4. Seasonal Adjustment and Forecasting
5. Forecasting with Transfer Function Models
6. Forecasting with Intervention Models
7. Foreca…

0. A gentle Introduction to Time Series Analysis, may serve as fast learning materials:

http://www.itl.nist.gov/div898/handbook/pmc/section4/pmc4.htm

1. An open source book(with data and code), A First Course on Time Series Analysis: examples with SAS, by Prof. Michael Falk, is available in:

http://statistik.mathematik.uni-wuerzburg.de/timeseries/

2. A SAS User book, Forecasting Examples for Business and Economics Using SAS by B. Cohen (another popular SAS User book for time series is SAS for Forecasting Time Series by John Brocklebank and David Dickey), is example-driven approach. You can review and submit the codes to learn SAS for time series analysis in a comprehensive way–there are 30 examples available:

1. Forecasting an Autoregressive Progress
2. Forecasting a Moving Average Process
3. Forecasting a Seasonal Process
4. Seasonal Adjustment and Forecasting
5. Forecasting with Transfer Function Models
6. Forecasting with Intervention Models
7. Forecasting Multivariate Time Series
8. Preparing Time Series Data for Forecasting
9. Using Macros for Forecasting Tasks
10. Fitting and Forecasting a Linear Model by OLS
11. Testing Forecasting Models for Break Points with Chow Tests
12. Fitting and Forecasting Linear Models with Linear Restrictions
13. Fitting and Forecasting a Linear Model with an AR Error Correction
14. Fitting Linear Models with Heteroscedastic Error Terms
15. Fitting Linear Models with ARCH-GARCH Error Terms
16. Assessing Forecast Accuracy
17. Forecasting Using a Lagged Dependent Variable Model
18. Static and Dynamic Forecasting Using a Lagged Dependent Variable Model
19. Fitting and Forecasting Polynomial Distributed Lag Models
20. Fitting and Forecasting Restricted Polynomial Distributed Lag Models
21. Fitting and Forecasting a Linear System by SUR and ITSUR
22. Testing and Restricting Parameter Estimates in a Linear System Forecast
23. Producing Goodness-of-Fit Statistics for Forecasts of a Linear System o
24. Fitting a Linear System by Instrumental Methods
25. Linear System Diagnostics and Autoregressive Error Correction
26. Creating Forecast confidence Limits with Monte Carlo Simulation
27. Fitting and Forecasting a Nonlinear Model
28. Restricting and Testing Parameters of a Nonlinear Forecasting Model
29. Producing Forecasts Automatically Using the Time Series Forecasting Sys
30. Developing Forecasting Models Using the Time Series Forecasting System

You can get the code with data and proc steps in SAS website:

http://ftp.sas.com/samples/A55512

3. SAS/ETS User’s Guide and Procedure Guide in SAS Product Documentation:

http://support.sas.com/documentation/onlinedoc/ets/index.html

JiangtangHu February 5, 2009
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