options(repos = c(getOption(“repos”),CRAN = “http://cran.uk.r-project.org”)) ]]>

Norman Matloff’s The Art of R Programming, a tour of statisical software design. ]]>

Same as you I had zero Bayesian influence during my undergrad years and my PhD didn’t consider Bayesian-thinking nor MCMC methods. So when I started having the need to go beyond pure likelihood-based approaches I suddenly found the need to fill the gap on MCMC methodology. At that point (3 years ago) THE reference I was pointed to was the Gamerman book. And I am sorry to say that it was a complete lost of time. I found it very badly written and absolutely not the first reference I would pick up should I ever suggest a monography on Monte Carlo (Markov Chain) methods. The fact that, up to a few years ago, it was one of the few books containing simultaneously the words “Monte Carlo” and “Markov Chain” made it a natural reference to suggest. But, oh boy! I found really hard to start understanding MCMC with it. Much better the classic ( and older) monography by Gilks-Richardson-Spiegelhalter or the very new (amazing IMHO) “Handbook of Markov Chain Monte Carlo” edited by Brooks-Gelman-Jones-Li Meng (2011).

]]>2. Of course you should use every resource, but I suspect that a low-end nvidia card would only give the same speed-ups as the multi-core processors on the laptop.

Don’t get me wrong – I think that GPUs are useful and can provide good speed-ups. But they can’t be used for every problem.

]]>2) It is also often the case that a low end nvidia card is available, especially in laptops. Why not use every resource available?

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