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Re: MCMC in Mathematica

  • To: mathgroup at smc.vnet.net
  • Subject: [mg96036] Re: MCMC in Mathematica
  • From: Asim <maa48 at columbia.edu>
  • Date: Mon, 2 Feb 2009 06:21:29 -0500 (EST)
  • References: <gm0q4e$rmq$1@smc.vnet.net>

On Jan 31, 1:12 am, Ramiro <ramiro.barran... at gmail.com> wrote:
> Hello,
>
> I use Mathematica a lot and now I would like to do MCMC to work on
> some of my problems.  Is this something that people with experience
> would recommend?  Or should I move to a different programming language
> such as C++ or R?  I have done a little samples of MCMC on mathematica
> and it does not take much code to get it running, but I am wondering
> if I would be better off in the long-run to work on something that
> would be faster.
>
> Thank you,
> Ramiro

Hi Ramiro

The choice between Mathematica and C or C++ depends upon the type of
statistical models you want to estimate, and the size of the data sets
you have in mind. If you are thinking of panel data situations and
nonlinear models with many latent variables and large data sets, then
C would be a better outcome. There is, often, no way to avoid loops in
MCMC, and this slows down stuff in Mathematica  as well as R
considerably because of their interpreted nature.

In my own work, I use the Gnu Scientific Library in C, as it allows
the use of BLAS for matrix algebra, and has almost all the random
variables you need in a MCMC situation. Of course, using C means more
work in allocation and deallocation of matrices etc, but I have found
it to be very useful because no project really needs running something
only once. Over repeated runs, and different model specifications, the
speed of C is a distinct advantage for complex models and large data
situations.

Mathematica and R are similar is speed, but R has more packages
available for Bayesian analysis, and for statistics in General. Of
course, Mathematica has the better interface.

Have fun

Asim Ansari



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