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Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics
ISBN-13:
9780387227641
Veröffentl:
2006
Seiten:
740
Autor:
Daniel Sorensen
Serie:
Statistics for Biology and Health
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
Beschreibung:
Review of Probability and Distribution Theory.- Uncertainty, Random Variables, and Probability Distributions.- Uncertainty about Functions of Random Variables.- Methods of Inference.- An Introduction to Likelihood Inference.- Further Topics in Likelihood Inference.- An Introduction to Bayesian Inference.- Bayesian Analysis of Linear Models.- The Prior Distribution and Bayesian Analysis.- Bayesian Assessment of Hypotheses and Models.- Approximate Inference Via the EM Algorithm.- Markov Chain Monte Carlo Methods.- An Overview of Discrete Markov Chains.- Markov Chain Monte Carlo.- Implementation and Analysis of MCMC Samples.- Applications in Quantitative Genetics.- Gaussian and Thick-Tailed Linear Models.- Threshold Models for Categorical Responses.- Bayesian Analysis of Longitudinal Data.- to Segregation and Quantitative Trait Loci Analysis.
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