An additional recommendation:
Information Theory, Inference, and Learning Algorithms (David MacKay, CUP 2003)
Free online at:
http://www.inference.phy.cam.ac.uk/mackay/itila/
Keith
Dr. Keith M. Briggs
Senior Mathematician, Complexity Research, BT Exact
http://more.btexact.com/people/briggsk2/ (internet)
http://research.btexact.com/teralab/keithbriggs.html (BT intranet)
phone: +44(0)1473 work: 641 911 home: 610 517 fax: 642 161
mail: Keith Briggs, Polaris 134, Adastral Park, Martlesham, Suffolk IP5 3RE, UK
-----Original Message-----
From: A UK-based worldwide e-mail broadcast system mailing list
[mailto:[log in to unmask]]On Behalf Of Allan Reese
Sent: 06 January 2004 15:28
To: [log in to unmask]
Subject: Summary of responses on introducing Bayesian statistics to
biologists
In tidying up 2003's emails, I was reminded that the question appeared on
allstat but the responses did not, as they were sent only to those who had
responded. The summary is worth adding to the archive.
On Fri, 18 Jul 2003, Chris Theobald wrote:
> Thank you for your responses, many of which took the form 'I would be
> grateful for any recommendations you receive'.
>
>
> To remind you, my query was
>
> I would be very grateful if anyone can recommend one or more articles
> or chapters giving an introduction to Bayesian statistics suitable for
> a numerate biologist. It (or they) should preferably include some
> reference to decision making and hierarchical modelling. Please send
> suggestions to me, not the list.
>
> I am looking for such an article because I am collaborating with some
> agronomists on optimizing the management of a food crop, and using
> trial data for several varieties and environments. My collaborators
> know how to fit a separate non-linear model by least squares for each
> combination of variety and environment, but not about likelihood, for
> example.
>
>
> The following books were recommended: the number recommending each is
> given in brackets.
>
> Carlin,BP & Louis,TA Bayes and Empirical Bayes Methods for Data
> Analysis [1]
> Cowan,G Statistical Data Analysis [1]
> Gatsonis,C Case Studies in Bayesian Statistics (5 vols) [1]
> Gelman,A et al Bayesian Data Analysis (2nd ed due out soon) [1]
> Gilks,WR et al MCMC in Practice [1]
> Jensen,FV Bayesian Networks [1]
> Lee,PM Bayesian Statistics: an Introduction (2nd ed) [2]
> Sivia,DS Data Analysis: A Bayesian Tutorial [2]
>
> I have not looked at the 'Case Studies', but none of the others seem to
> be intended for biologists: Cowan and Sivia are written for physical
> scientists.
>
>
> The links I was sent were as follows.
>
> http://www.shef.ac.uk/chebs/ includes an elementary introduction to
> Bayesian statistics and its application in health economics
>
> http://darwin.eeb.uconn.edu/summer-institute/summer-institute.html
> includes notes on Bayesian approaches to analysis of population genetic
> data
>
>
> The following come from a Google search: I have merely removed the
> duplicates and a missing link.
>
> http://www.cs.toronto.edu/~radford/review.abstract.html
> http://www.cs.toronto.edu/~radford/res-mcmc.html
> http://jackman.stanford.edu/mcmc/index.html
> http://www.telecom.csuhayward.edu/~stat/Gibbs/index.html
> http://www.cs.berkeley.edu/~murphyk/Bayes/bayes.html#reading
> http://www.bayes.com/
> http://www.mysoe.net/
> http://www.stats.bris.ac.uk/~peter/Research.html
> http://www.wiley.com/cda/product/0,,0471496006|print|2738,00.html
> http://www.mrc-bsu.cam.ac.uk/bugs/
> http://www.bayesian.org/books/books.html
> http://www.stat.duke.edu/~dalene/talks/ncssm/index.htm
> http://kmi.open.ac.uk/projects/bkd/
> http://www.stat.ucla.edu/~jsanchez/sbssnews/sbssnews.html
> http://www.bayesian.org/
>
>
> Chris Theobald
