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- Author: Marc Kéry
- Publisher: Elsevier
- ISBN-10: 0443137153
- ISBN-13: 9780443137150
- Format: 19.1 x 23.5 x 2.8 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
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Description
Applied Statistical Modelling for Ecologists: A Practical Guide to Bayesian and Likelihood Inference Using R, JAGS/Nimble, Stan and TMB provides an important guide and comparison of the powerful new software packages, such as JAGS, Stan, Nimble, and TMB, that are now widely used in research publications.
In addition, this book is simple and accessible, allowing researchers to carry out and understand statistical modeling, provides a gentle introduction to the most exciting, specialist software with which this "statistical learning from data" is often done in current cutting-edge research along with Bayesian statistics and frequentist statistics with its maximum likelihood estimation method.
Though the examples in Applied Statistical Modelling for Ecologists: A Practical Guide to Bayesian and Likelihood Inference Using R, JAGS/Nimble, Stan and TMB will come from ecology and environmental science, the underlying statistical models are widely used by scientists across many disciplines. Thus, this book will be useful for anybody who needs to learn and to quickly become proficient in statistical modeling and in the model-fitting engines covered.
EXTRA 10 % discount with code: EXTRA
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- Author: Marc Kéry
- Publisher: Elsevier
- ISBN-10: 0443137153
- ISBN-13: 9780443137150
- Format: 19.1 x 23.5 x 2.8 cm, softcover
- Language: English English
Applied Statistical Modelling for Ecologists: A Practical Guide to Bayesian and Likelihood Inference Using R, JAGS/Nimble, Stan and TMB provides an important guide and comparison of the powerful new software packages, such as JAGS, Stan, Nimble, and TMB, that are now widely used in research publications.
In addition, this book is simple and accessible, allowing researchers to carry out and understand statistical modeling, provides a gentle introduction to the most exciting, specialist software with which this "statistical learning from data" is often done in current cutting-edge research along with Bayesian statistics and frequentist statistics with its maximum likelihood estimation method.
Though the examples in Applied Statistical Modelling for Ecologists: A Practical Guide to Bayesian and Likelihood Inference Using R, JAGS/Nimble, Stan and TMB will come from ecology and environmental science, the underlying statistical models are widely used by scientists across many disciplines. Thus, this book will be useful for anybody who needs to learn and to quickly become proficient in statistical modeling and in the model-fitting engines covered.
Reviews