Re: st: How to compute with Stata probabilities by conditioning ?

["Roger B. Newson" <r.newson@imperial.ac.uk>]

If you type, in Stata,

help density_functions##normal

then you will find that the function binormal(h,k,r) computes the joint 
cumulative distribution function, not the conditional diatribution 
function as you seem to believe. The .pdf documentatio gives the 
equation explicitly.

I hope this helps.

Best wishes

Roger

Roger B Newson BSc MSc DPhil
Lecturer in Medical Statistics
Respiratory Epidemiology and Public Health Group
National Heart and Lung Institute
Imperial College London
Royal Brompton Campus
Room 33, Emmanuel Kaye Building
1B Manresa Road
London SW3 6LR
UNITED KINGDOM
Tel: +44 (0)20 7352 8121 ext 3381
Fax: +44 (0)20 7351 8322
Email: r.newson@imperial.ac.uk
Web page: http://www.imperial.ac.uk/nhli/r.newson/
Departmental Web page:
http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/popgenetics/reph/

Opinions expressed are those of the author, not of the institution.

On 17/05/2013 15:52, Tiago V. Pereira wrote:
> Dear statalisters,
>
> Imagine two standard normal variables, X and Y, with known correlation, rho.
>
> P(X>t1|Y>t2) can be computed with
>
> binormal(t1,t2,rho)
>
> What if we were interest in computing
>
> P(X>t1 and Y>t2) ?
>
> Since X and Y are correlated, I am a bit confused.
>
> I am using brute force (dumb way):
>
> set obs 1000000000
> matrix M = (1,rho \ rho, 1)
> drawnorm x y, means(0 0) sds(1 1) corr(M)
> count if x>t1&y>t2
>
> P(X>t1 and Y>t2)  = r(N)/_N
>
> Is there a smarter way of computing probabilities by conditioning (with
> Stata)?
>
> Thanks in advance.
>
> Tiago
>
>
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/faqs/resources/statalist-faq/
> *   http://www.ats.ucla.edu/stat/stata/
*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/faqs/resources/statalist-faq/
*   http://www.ats.ucla.edu/stat/stata/