Bayesian Methods for Statistical Analysis.
Puza, Borek.
Bayesian Methods for Statistical Analysis. - 1 online resource
Includes bibliographical references.
1. Bayesian basics part 1 -- 2. Bayesian basics part 2 -- 3. Bayesian basics part 3 -- 4. Computational tools -- 5. Monte Carlo basics -- 6. MCMC methods part 1 -- 7. MCMC methods part 2 -- 8. Inference via WinBUGS -- 9. Bayesian finite population theory -- 10. Normal finite population models -- 11. Transformations and other topics -- 12. Biased sampling and nonresponse -- Appendix A: Additional exercises -- Appendix B: Distributions and notation -- Appendix C: Abbreviations and acronyms.
Bayesian methods for statistical analysis¡is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse. The book contains many exercises, all with worked solutions, including complete computer code. It is suitable for self-study or a semester-long course, with three hours of lectures and one tutorial per week for 13 weeks.
English.
9781921934254 1921934255 1921934263 9781921934261
10.26530/OAPEN_611011 doi
22573/ctt1bh26x1 JSTOR
Bayesian statistical decision theory.
Mathematics.
Probability & statistics.
Bayesian inference.
Mathematics / Probability & Statistics / Bayesian Analysis.
Mathematics / Probability & Statistics.
Mathematics.
Bayesian statistical decision theory.
statistics. mathematics. bayesian inference. probability.
Electronic books.
QA279.5 / .B39 2015eb
519.5/42
Bayesian Methods for Statistical Analysis. - 1 online resource
Includes bibliographical references.
1. Bayesian basics part 1 -- 2. Bayesian basics part 2 -- 3. Bayesian basics part 3 -- 4. Computational tools -- 5. Monte Carlo basics -- 6. MCMC methods part 1 -- 7. MCMC methods part 2 -- 8. Inference via WinBUGS -- 9. Bayesian finite population theory -- 10. Normal finite population models -- 11. Transformations and other topics -- 12. Biased sampling and nonresponse -- Appendix A: Additional exercises -- Appendix B: Distributions and notation -- Appendix C: Abbreviations and acronyms.
Bayesian methods for statistical analysis¡is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse. The book contains many exercises, all with worked solutions, including complete computer code. It is suitable for self-study or a semester-long course, with three hours of lectures and one tutorial per week for 13 weeks.
English.
9781921934254 1921934255 1921934263 9781921934261
10.26530/OAPEN_611011 doi
22573/ctt1bh26x1 JSTOR
Bayesian statistical decision theory.
Mathematics.
Probability & statistics.
Bayesian inference.
Mathematics / Probability & Statistics / Bayesian Analysis.
Mathematics / Probability & Statistics.
Mathematics.
Bayesian statistical decision theory.
statistics. mathematics. bayesian inference. probability.
Electronic books.
QA279.5 / .B39 2015eb
519.5/42