Likelihood Methods in Biology and Ecology PDF Download
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Author: Michael Brimacombe
Publisher: CRC Press
ISBN: 0429533233
Category : Mathematics
Languages : en
Pages : 274
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Book Description
This book emphasizes the importance of the likelihood function in statistical theory and applications and discusses it in the context of biology and ecology. Bayesian and frequentist methods both use the likelihood function and provide differing but related insights. This is examined here both through review of basic methodology and also the integr
Author: Michael Brimacombe
Publisher: CRC Press
ISBN: 0429533233
Category : Mathematics
Languages : en
Pages : 274
Get Book Here
Book Description
This book emphasizes the importance of the likelihood function in statistical theory and applications and discusses it in the context of biology and ecology. Bayesian and frequentist methods both use the likelihood function and provide differing but related insights. This is examined here both through review of basic methodology and also the integr
Author: Leonhard Held
Publisher: Springer Nature
ISBN: 3662607921
Category : Medical
Languages : en
Pages : 409
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Book Description
This richly illustrated textbook covers modern statistical methods with applications in medicine, epidemiology and biology. Firstly, it discusses the importance of statistical models in applied quantitative research and the central role of the likelihood function, describing likelihood-based inference from a frequentist viewpoint, and exploring the properties of the maximum likelihood estimate, the score function, the likelihood ratio and the Wald statistic. In the second part of the book, likelihood is combined with prior information to perform Bayesian inference. Topics include Bayesian updating, conjugate and reference priors, Bayesian point and interval estimates, Bayesian asymptotics and empirical Bayes methods. It includes a separate chapter on modern numerical techniques for Bayesian inference, and also addresses advanced topics, such as model choice and prediction from frequentist and Bayesian perspectives. This revised edition of the book “Applied Statistical Inference” has been expanded to include new material on Markov models for time series analysis. It also features a comprehensive appendix covering the prerequisites in probability theory, matrix algebra, mathematical calculus, and numerical analysis, and each chapter is complemented by exercises. The text is primarily intended for graduate statistics and biostatistics students with an interest in applications.
Author: Bill Shipley
Publisher: Cambridge University Press
ISBN: 9780521529211
Category : Mathematics
Languages : en
Pages : 330
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Book Description
This book goes beyond the truism that 'correlation does not imply causation' and explores the logical and methodological relationships between correlation and causation. It presents a series of statistical methods that can test, and potentially discover, cause-effect relationships between variables in situations in which it is not possible to conduct randomised or experimentally controlled experiments. Many of these methods are quite new and most are generally unknown to biologists. In addition to describing how to conduct these statistical tests, the book also puts the methods into historical context and explains when they can and cannot justifiably be used to test or discover causal claims. Written in a conversational style that minimises technical jargon, the book is aimed at practising biologists and advanced students, and assumes only a very basic knowledge of introductory statistics.
Author: Benjamin M. Bolker
Publisher: Princeton University Press
ISBN: 0691125228
Category : Computers
Languages : en
Pages : 408
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Book Description
Introduction and background; Exploratory data analysis and graphics; Deterministic functions for ecological modeling; Probability and stochastic distributions for ecological modeling; Stochatsic simulation and power analysis; Likelihood and all that; Optimization and all that; Likelihood examples; Standar statistics revisited; Modeling variance; Dynamic models.
Author: Michael A. McCarthy
Publisher: Cambridge University Press
ISBN: 113946387X
Category : Science
Languages : en
Pages : 310
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Book Description
The interest in using Bayesian methods in ecology is increasing, however many ecologists have difficulty with conducting the required analyses. McCarthy bridges that gap, using a clear and accessible style. The text also incorporates case studies to demonstrate mark-recapture analysis, development of population models and the use of subjective judgement. The advantages of Bayesian methods, are also described here, for example, the incorporation of any relevant prior information and the ability to assess the evidence in favour of competing hypotheses. Free software is available as well as an accompanying web-site containing the data files and WinBUGS codes. Bayesian Methods for Ecology will appeal to academic researchers, upper undergraduate and graduate students of Ecology.
Author: Justin Kitzes
Publisher: University of Chicago Press
ISBN: 0226818330
Category : Nature
Languages : en
Pages : 174
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Book Description
An essential guide to quantitative research methods in ecology and conservation biology, accessible for even the most math-averse student or professional. Quantitative research techniques have become increasingly important in ecology and conservation biology, but the sheer breadth of methods that must be understood—from population modeling and probabilistic thinking to modern statistics, simulation, and data science—and a lack of computational or mathematics training have hindered quantitative literacy in these fields. In this book, ecologist Justin Kitzes addresses those challenges for students and practicing scientists alike. Requiring only basic algebra and the ability to use a spreadsheet, Handbook of Quantitative Ecology is designed to provide a practical, intuitive, and integrated introduction to widely used quantitative methods. Kitzes builds each chapter around a specific ecological problem and arrives, step by step, at a general principle through the process of solving that problem. Grouped into five broad categories—difference equations, probability, matrix models, likelihood statistics, and other numerical methods—the book introduces basic concepts, starting with exponential and logistic growth, and helps readers to understand the field’s more advanced subjects, such as bootstrapping, stochastic optimization, and cellular automata. Complete with online solutions to all numerical problems, Kitzes’s Handbook of Quantitative Ecology is an ideal coursebook for both undergraduate and graduate students of ecology, as well as a useful and necessary resource for mathematically out-of-practice scientists.
Author: David R. Anderson
Publisher: Springer Science & Business Media
ISBN: 0387740759
Category : Science
Languages : en
Pages : 203
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Book Description
This textbook introduces a science philosophy called "information theoretic" based on Kullback-Leibler information theory. It focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The text is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals. Readers are however expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation.
Author: Ruth King
Publisher: CRC Press
ISBN: 1439811881
Category : Mathematics
Languages : en
Pages : 457
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Book Description
Emphasizing model choice and model averaging, this book presents up-to-date Bayesian methods for analyzing complex ecological data. It provides a basic introduction to Bayesian methods that assumes no prior knowledge. The book includes detailed descriptions of methods that deal with covariate data and covers techniques at the forefront of research, such as model discrimination and model averaging. Leaders in the statistical ecology field, the authors apply the theory to a wide range of actual case studies and illustrate the methods using WinBUGS and R. The computer programs and full details of the data sets are available on the book's website.
Author: Scott Ferson
Publisher: Springer Science & Business Media
ISBN: 0387954864
Category : Nature
Languages : en
Pages : 334
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Book Description
Reviews the quantitative tools used in the study of subjects such as biodiversity, resource management and endangered species preservation. Topics covered include population viability analysis, population dynamics, metapopulation models, estimating timing of extinctions, quasi-extinction and more.
Author: Leonhard Held
Publisher: Springer Science & Business Media
ISBN: 3642378870
Category : Mathematics
Languages : en
Pages : 381
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Book Description
This book covers modern statistical inference based on likelihood with applications in medicine, epidemiology and biology. Two introductory chapters discuss the importance of statistical models in applied quantitative research and the central role of the likelihood function. The rest of the book is divided into three parts. The first describes likelihood-based inference from a frequentist viewpoint. Properties of the maximum likelihood estimate, the score function, the likelihood ratio and the Wald statistic are discussed in detail. In the second part, likelihood is combined with prior information to perform Bayesian inference. Topics include Bayesian updating, conjugate and reference priors, Bayesian point and interval estimates, Bayesian asymptotics and empirical Bayes methods. Modern numerical techniques for Bayesian inference are described in a separate chapter. Finally two more advanced topics, model choice and prediction, are discussed both from a frequentist and a Bayesian perspective. A comprehensive appendix covers the necessary prerequisites in probability theory, matrix algebra, mathematical calculus, and numerical analysis.
