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Lieferstatus:	i.d.R. innert 14-24 Tagen versandfertig
Veröffentlichung:	Juni 1996
Genre:	Schulbücher
ISBN:	9780387946887
EAN-Code:	9780387946887
Verlag:	Springer New York
Einband:	Gebunden
Sprache:	English
Dimensionen:	H 241 mm / B 160 mm / D 18 mm
Gewicht:	500 gr
Seiten:	220
Zus. Info:	HC runder Rücken kaschiert
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

This book provides a unified introduction to a variety of computational algorithms for Bayesian and likelihood inference. In this third edition, I have attempted to expand the treatment of many of the techniques discussed. I have added some new examples, as well as included recent results. Exercises have been added at the end of each chapter. Prerequisites for this book include an understanding of mathematical statistics at the level of Bickel and Doksum (1977), some understanding of the Bayesian approach as in Box and Tiao (1973), some exposure to statistical models as found in McCullagh and NeIder (1989), and for Section 6. 6 some experience with condi­ tional inference at the level of Cox and Snell (1989). I have chosen not to present proofs of convergence or rates of convergence for the Metropolis algorithm or the Gibbs sampler since these may require substantial background in Markov chain theory that is beyond the scope of this book. However, references to these proofs are given. There has been an explosion of papers in the area of Markov chain Monte Carlo in the past ten years. I have attempted to identify key references-though due to the volatility of the field some work may have been missed.