Hi all,
does anyone know a quick (or not so quick) way to generate
random deviates from a mixture of distributions? I'd like to
generate a random multivariate sample - one variable is
normally distributed and the other two Bernoulli - with a
specific var-covar matrix. If all variables were normal, I
could just use mvtnorm(). But what can I do in this case? (I
thought about using Metropolis-Hastings or something like
this, but maybe there is a better way of doing this...?) Any
suggestions would be very welcome.
cheers,
Holger
--
Holger Lutz Kern
Graduate Student
Department of Government
Cornell University
Institute for Quantitative Social Science
Harvard University
1737 Cambridge Street N350
Cambridge, MA 02138
www.people.cornell.edu/pages/hlk23