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From |
"Chris Chung" <[email protected]> |

To |
<[email protected]> |

Subject |
st: Re: draw parameter values from distribution |

Date |
Tue, 14 Dec 2004 05:15:33 -0500 |

Dear Hans,

I had a similar problem. My problem was related to the size of dataset and time-consuming computing procedure (i.e. multiple failure-time analysis). Although I used a quad xeon 2.2 processor with 8 GB of RAM and 500 GB of drive space, I had to wait several days to get the result of multiple failure-time analysis. I was really surprised by the slow computing speed as I have yet to run more complicated models with more variables. However, the 2 GB limit that we are experiencing is a Stata/Terminal Services limitation (or feature). Any single application running through Stata/Terminal Services can only allocate up to 2 GB of memory. In this case, with a 32 bit application it doesn't really matter - the current 32 bit Stata for Windows can only allocate a theoretical 2 GB of memory anyway. When MS officially releases a 64 bit version of Windows, we will have a 64 bit compile of Stata for Windows which will be able to overcome the 2 GB limit. But the time has not come yet.

Chris

----- Original Message ----- From: "Kelchtermans, Stijn" <[email protected]>

To: <[email protected]>

Sent: Tuesday, December 14, 2004 4:25 AM

Subject: st: draw parameter values from distribution

All,

I'm estimating a conditional logit model of schooling choice. I want to obtain confidence intervals for the predicted choice probabilities.

The approach I want to use is the following:

based on the parameter estimates, get 1000 draws from the multivariate normal distribution to generate 1000 alternative parameter values. Using these values, I calculate 1000 choice probabilities. I then drop 2,5% of the values in each tail to get the 95% CI for the choice probabilities.

I can't find Stata commands that allow to automate this procedure. If I use "drawnorm" to get the parameter value, I lose the dataset so I can't calculate the predicted probabilities. The best I can think of is to put the parameter draws in a matrix, read the dataset again and then calculate the probabilities. This seems quite a hassle to program though.

Any ideas to simplify this?

Many thanks,

Stijn Kelchtermans

Katholieke Universiteit Leuven

Belgium

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**Follow-Ups**:**Re: st: Re: draw parameter values from distribution***From:*"Neil Shephard" <[email protected]>

**References**:**st: draw parameter values from distribution***From:*"Kelchtermans, Stijn" <[email protected]>

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