Monte Carlo Statistical Methods (Springer Texts in Statistics)

Casella, George,Robert, Christian P.

ISBN 10: 038798707X / ISBN 13: 9780387987071

Verlag: Springer Verlag, 1999

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Inhaltsangabe:

Monte Carlo statistical methods, particularly those based on Markov chains, have now matured to be part of the standard set of techniques used by statisticians. This book is intended to bring these techniques into the class­ room, being (we hope) a self-contained logical development of the subject, with all concepts being explained in detail, and all theorems, etc. having detailed proofs. There is also an abundance of examples and problems, re­ lating the concepts with statistical practice and enhancing primarily the application of simulation techniques to statistical problems of various dif­ ficulties. This is a textbook intended for a second-year graduate course. We do not assume that the reader has any familiarity with Monte Carlo techniques (such as random variable generation) or with any Markov chain theory. We do assume that the reader has had a first course in statistical theory at the level of Statistical Inference by Casella and Berger (1990). Unfortu­ nately, a few times throughout the book a somewhat more advanced no­ tion is needed. We have kept these incidents to a minimum and have posted warnings when they occur. While this is a book on simulation, whose actual implementation must be processed through a computer, no requirement is made on programming skills or computing abilities: algorithms are pre­ sented in a program-like format but in plain text rather than in a specific programming language. (Most of the examples in the book were actually implemented in C, with the S-Plus graphical interface.

Über die Autorin bzw. den Autor: Christian P. Robert is Professor of Statistics in the Mathematics Department at the University of Rouen, France. He is also Head of the Statistics Laboratory at the Center for Research in Economics and Statistics (CREST) of the National Institute for Statistics and Economic Studies (INSEE) in Paris, and lecturer at Ecole Polytechnique. He has written three other books, including The Bayesion Choice, Springer, 1994. He also edited Discretization and MCMC Convergence Assessment, Springer, 1998. He has served as an associate editor for the Annals of Statistics and the Journal of the American Statistical Association. He is a fellow of the Institute of Mathematical Statistics, and a winner of the Young Statistician Award of the So66t6 de Statistique de Paris in 1995. George Casella is the liberty Hyde Bailey Professor of Biological Statistics in the College of Agriculture and life Sciences at Cornell University. He has served as the Theory and Methods Editor of the Journal of the American Statistical Association. He has authored three other textbooks: Statistical Inference, 1990, with Roger L. Berger; Variance Components, 1992, with Shayle R. Searle and Charles E. McCulloch; and Theory of Point Estimation, Second Edition, 1998, with Erich Lehmann. He is a fellow of the Institute of Mathematical Statistics and the American Statistical Association, and an elected fellow of the International Statistical Institute.

Bibliografische Details

Titel: Monte Carlo Statistical Methods (Springer ...
Verlag: Springer Verlag
Erscheinungsdatum: 1999
Einband: Hardcover
Zustand: Good