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Product details
File Size: 13698 KB
Print Length: 315 pages
Publisher: Academic Press; 1 edition (April 4, 2015)
Publication Date: April 4, 2015
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B00W18O078
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#1,127,618 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
I am not an ecological modeler, but work and teach in other areas of statistics. I have developed an interest in ecological models.This book is a survey of the subject with broad coverage. The book contains a lot of great material. The authors compare frequentist methods to Bayesian methods for most major model types. There are plenty of bibliographic references if you want to follow up in-depth.Be prepared to spend a fair amount of time digesting this material. The discussion is often terse and the explanations of some theory are are bit brief; hence the 4 star review. The code examples are very helpful in understanding what the authors are talking about. I am sure it was difficult for the authors to provide both a good overview of the models used and the application to ecology in the same book
Perfect.
I am not an ecologist - and so, for example, I can only marvel at such intellectual pursuits as statistical modeling of sea slug's sperm volume, recounted on page 170. (That Anthes et al. (2014) paper must have had the Ig Nobel prize in the bag). However, only one chapter of “Bayesian Data Analysis in Ecology†is ecology-focused - and even that material is useful to a non-ecologist, as an example of a complex BUGS or STAN model. Nor is the book relevant just for people interested in Bayesian statistics - again, Bayesian matters account for only a small proportion of the total page count, in the book's final chapters. What I see is a gentle, nicely presented, R-illustrated intermediate-level course in mixed models, which feels like an extension of “Data Analysis Using Regression and Multilevel/Hierarchical Models†by Gelman and Hill. Just like that book is Bayesian only where it needs to be, “Bayesian Data Analysis in Ecology†does not focus on Bayesian methods, but introduces Bayesian analyses after a tour of the “mainstream†aproach. The overall impression is very positive, and it is unfortunate that the book's reach may be limited by the accurate-yet-too-specific title, and the publisher's rather greedy pricing.
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