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Ecological Models and Data in R (Englisch) Gebundene Ausgabe – 1. Juli 2008

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"Bolker's book is a must-buy for anyone wanting to fit data to models and go beyond hypothesis testing, but it is certainly not an 'introductory' text in the sense of 'simple'. This book is a tour de force for anyone who studied ecology for his or her interest of nature's working. But it is the one single book that can propel the statistical novice to the cutting edge of statistical ecology--albeit with blood, sweat and tears."--Carsten F. Dormann, Basic and Applied Ecology "[A] must for natural scientists and for statisticians who are interested in ecological applications... Numerous enlightening footnotes, meaningful graphics and direct speech are evidence of substantial classroom experience of the author... The book addresses students and researchers who have or have had some basic knowledge in ecology, mathematics and statistics. Delivering many examples and profound details on numerical aspects of maximum likelihood estimation, the book may also give a red line for a course in computational statistics."--Martin Schlather, Biometrical Journal "[T]his book succeeds both in explaining how to analyze many types of ecological data, and in clearly describing the theoretical background behind some common analyses and approaches. I expect to refer to it often."--Lynda D. Prior, Austral Ecology


"Ecological Models and Data in R" is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, this book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood, information-theoretic, and Bayesian techniques to analyze their own data using the programming language R. Drawing on extensive experience teaching these techniques to graduate students in ecology, Benjamin Bolker shows how to choose among and construct statistical models for data, estimate their parameters and confidence limits, and interpret the results.This book also covers statistical frameworks, the philosophy of statistical modeling, and critical mathematical functions and probability distributions. It requires no programming background - only basic calculus and statistics.

It offers: practical, beginner-friendly introduction to modern statistical techniques for ecology using the programming language R; step-by-step instructions for fitting models to messy, real-world data; a balanced view of different statistical approaches; wide coverage of techniques - from simple (distribution fitting) to complex (state-space modeling); techniques for data manipulation and graphical display; and, a companion web site with data and R code for all examples.

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15 von 15 Kunden fanden die folgende Rezension hilfreich
An excellent resource for ecologists 10. März 2009
Von James R. Vonesh - Veröffentlicht auf
Format: Gebundene Ausgabe
This book, in part, was developed from Dr. Bolker's graduate course in Ecological Models and Data at the University of Florida. This was the best course I took as a graduate student, it transformed the set of quantitative tools I was able to bring to bear on ecological questions. There was so much worthwhile material covered in this class that I took it twice (UF only counted the first time:). Since graduate school I still frequently refer to my notes from the class. With the publication of "Ecological Models and Data in R" even those who didn't have the good fortune of being in Bolker's class can learn approaches for integrating ecological theory and data. Bolker's book covers much of the material from his course and thus is an excellent resource for graduate students and faculty alike.
9 von 9 Kunden fanden die folgende Rezension hilfreich
Great hands-on textbook 28. Oktober 2009
Von ah - Veröffentlicht auf
Format: Gebundene Ausgabe
I'm doing infectious disease modeling for a living, and I got a lot out of this book. I was not too familiar with R and with stochastic models. Reading and working through this book taught me a lot. The book is really meant to be worked through carefully. Ben drops nuggets of wisdom everywhere - but you need to read carefully to catch them. It's not the ideal book if you need a quick reference on how to do "X". But as a textbook and to really learn things, it is great. That said, I would hesitate to use it for a real beginner's class. Some background with statistical concepts and a solid math foundation are necessary. And some programming experience, with either R or another language, helps a lot. If students are too weak in any of these areas, it would be hard to teach the material in a single semester course. But the great thing about this book is that anyone motivated to learn the subject matter can "simply" sit down and work through it on their own and at their own pace. It will take time, but it's totally worth it.
2 von 2 Kunden fanden die folgende Rezension hilfreich
Nice book 5. September 2008
Von Amazon Customer - Veröffentlicht auf
Format: Gebundene Ausgabe Verifizierter Kauf
I am a molecular biologist, trying to work my way through some ecological modeling. I found this book quite useful, since it has lot of examples and details. There is an online supplement for this book, where you can get all the scripts and pdf versions of the chapters, if you want. the R supplements, and the scripts give you a hands-on experience in handling the data in R. Tests like maximum likelihood, monte carlo are explained very well, and the R scripts help in understanding the nitty-gritties of programming. All in all, a good book.
1 von 1 Kunden fanden die folgende Rezension hilfreich
Cover a different selection of subjects 12. Juni 2012
Von Fred - Veröffentlicht auf
Format: Kindle Edition Verifizierter Kauf
For those who already had a good familiarity with R and general procedures of statistics, this book is a great choice, because cover different aspects of statistics compared with classics like "The R Book". Also a good choice for those biologists interested in a little deeper knowledge in mathematics
A terrific book on ecological modelling in R 12. April 2013
Von Dr Joseph A. Bulbulia - Veröffentlicht auf
Format: Gebundene Ausgabe Verifizierter Kauf
This is an excellent resource for anyone who wants to learn how to model GLMMs in R, complete with R code, graphs, worked examples, simulation methods & lots else. It is certainly a good introductory text, and doesn't assume too much by way of mathematical/statistical background. However, there's no shallow end to this book. I suspect even those who have mastered GLMMs will find it rewarding to return to this book time and again. Bolker's book is worth owning in my view.
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