[SciPy-User] [OT] Bayesian vs. frequentist

J. David Lee johnl@cs.wisc....
Wed Feb 15 10:47:53 CST 2012

On 02/15/2012 08:37 AM, Lou Pecora wrote:
> *From:* Daniele Nicolodi <daniele@grinta.net>
> *To:* scipy-user@scipy.org
> *Sent:* Wednesday, February 15, 2012 3:21 AM
> *Subject:* Re: [SciPy-User] [OT] Bayesian vs. frequentist
> Hello, I'll hijack this thread to ask for advice.
> I'm a physicist and, as you may expect, my education in statistics is
> mostly in Frequentists methods. However, I always had an interest in
> Bayesian methods, as those seems to solve in much more natural ways the
> problems that arise in complex data analysis.
> I recently started to read "Data Analysis, A Bayesian Tutorial" by D.S.
> Silva (currently reading chapter 4, unfortunately real work is always
> interfering) and I really like the approach and the straight forward
> manner in which the theory builds up.
> However, I feel that the Bayesian approach, is much more difficult to
> translate to practical methods I can implement, but I may be biased by
> the long term exposition to the "recipe based" Frequentist approach.
> Can someone suggest me some resources (documentation or code) where some
> practical approaches to Bayesian analysis are taught?
> Thank you. Cheers,
> -- 
> Daniele
> _______________________________________________
> SciPy-User mailing list
> I'm also a physicist and just getting into all this.  Silva's book is 
> good.  Here are two others I found that look good and readable.  I 
> have not read either all the way, but they are worth examining.  You 
> should also (after digesting some standard Bayesian statistics) 
> examine the newer latent Dirichlet methods which look pretty powerful 
> and seem to have a better way to handle and generate priors.  Again, 
> I'm a novice here, but these look like good avenues for a scientist 
> trying to learn Bayesian statistics.
> (1) Udo von Toussaint, "Bayesian inference in physics", REVIEWS OF 
> (2) Daniela Calvetti and Erkki Somersalo, Introduction to Bayesian 
> scientific computing (Springer, 2007)
> It's a good topic even if it's OT -- provided everyone remains civil. 
>  :-)
> -- Lou Pecora, my views are my own.
I would also recommend the Toussaint paper. It contains several case 
studies from various areas of physics that you might find interesting.

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