Bayesian Statistics: An Introduction, 4th Edition by Peter M. Lee
Requirements: .ePUB reader, 10 MB
Overview: Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques.
This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as well as how it contrasts with the conventional approach. The theory is built up step by step, and important notions such as sufficiency are brought out of a discussion of the salient features of specific examples.
Genre: Non-Fiction > Educational
Download Instructions:
https://userupload.net/n1arq2c6ks6j
https://dropgalaxy.vip/rc19u2hiw6k2
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Requirements: .ePUB reader, 10 MB
Overview: Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques.
This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as well as how it contrasts with the conventional approach. The theory is built up step by step, and important notions such as sufficiency are brought out of a discussion of the salient features of specific examples.
Genre: Non-Fiction > Educational
Download Instructions:
https://userupload.net/n1arq2c6ks6j
https://dropgalaxy.vip/rc19u2hiw6k2
Trouble downloading? Read This.