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Re: st: Model Selection and Choices


From   Paul Millar <paulmi@nipissingu.ca>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Model Selection and Choices
Date   Wed, 27 Apr 2011 12:41:46 -0400

Usually the BIC statistic (or alternately the AIC) is used for model
selection when the model uses maximum likelihood, using the
postestimation -estat(ic)- command.  Another method is the
Proportional Reduction in Errors (PRE) method (i.e. the model that has
the fewest errors in prediction).  There is a postestimation command
for this -pre- available from ssc, however, I am not sure I have
tested it for the type of time series models you are using.  -pre- has
the advantage of working for any model type.  If it doesn't seem to
work for the models you are using, send me the commands and a data
sample and I will get it working for you.

- Paul

On Wed, Apr 27, 2011 at 1:47 AM, Muhammad Anees <aneesmkhattak@gmail.com> wrote:
> Hi All!
>
> I have a straight question on time series modelling. I have a 37 years
> annualized time series data on five variables. I want to check if
> linear or non linear modelling would be best in my case. Is there any
> way using stata to obtain results and to select model that best
> reflects my specific time series data.
>
> --
> Muhammad Anees
> MSc in Economics
> The University of Sheffield
> United Kingdom
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>



-- 
- Paul Millar
Criminal Justice and Legal Studies
Nipissing University
North Bay, Ontario, Canada
www.paulmillar.ca

*
*   For searches and help try:
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