Research Catalog

Title

Likelihood, Bayesian and MCMC methods in quantitative genetics / Daniel Sorensen, Daniel Gianola.

Author

Sorensen, Daniel

Publication

New York : Springer, c2002.

Items in the Library & Off-site

Details

Additional Authors

Gianola, Daniel, 1947-

Description

xvii, 740 p.; 25 cm.

Series Statement

Statistics for biology and health

Uniform Title

Statistics for biology and health.

Subject

• Genetics > Statistical methods
• Monte Carlo method
• Markov processes
• Bayesian statistical decision theory
• Genetics > statistics & numerical data
• Monte Carlo Method
• Markov Chains

Bibliography (note)

• Includes bibliographical references (p. [701]-726) and index.

Contents

I. Review of Probability and Distribution Theory. 1. Probability and Random Variables. 2. Functions of Random Variables -- II. Methods of Inference. 3. An Introduction to Likelihood Inference. 4. Further Topics in Likelihood Inference. 5. An Introduction to Bayesian Inference. 6. Bayesian Analysis of Linear Models. 7. The Prior Distribution and Bayesian Analysis. 8. Bayesian Assessment of Hypotheses and Models. 9. Approximate Inference Via the EM Algorithm -- III. Markov Chain Monte Carlo Methods. 10. An Overview of Discrete Markov Chains. 11. Markov Chain Monte Carlo. 12. Implementation and Analysis of MCMC Samples -- IV. Applications in Quantitative Genetics. 13. Gaussian and Thick-Tailed Linear Models. 14. Threshold Models for Categorical Responses. 15. Bayesian Analysis of Longitudinal Data. 16. Segregation and Quantitative Trait Loci Analysis.

ISBN

0387954406 (alk. paper)

LCCN

2002019555

OCLC

• ocm48907138
• SCSB-4793267

Owning Institutions

Columbia University Libraries