Monte Carlo Statistical Methods
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-c
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Stephen Fienberg
Ingram Olkin
Springer Science+Business Media, LLC
Springer Texts in Statistics Alfred: Elements of Statistics for the Life and Social Sciences Berger: An Introduction to Probability and Stochastic Processes Bilodeau and Brenner: Theory of Multivariate Statistics Blom: Probability and Statistics: Theory and Applications Brockwell and Davis: An Introduction to Times Series and Forecasting Chow and Teicher: Probability Theory: Independence, Interchangeability, Martingales, Third Edition Christensen: Plane Answers to Complex Questions: The Theory of Linear Models, Second Edition Christensen: Linear Models for Multivariate, Time Series, and Spatial Data Christensen: Log-Linear Models and Logistic Regression, Second Edition Creighton: A First Course in Probability Models and Statistical Inference Dean and Voss: Design and Analysis of Experiments du Toit, Steyn, and Stump!" Graphical Exploratory Data Analysis Durrett: Essentials of Stochastic Processes Edwards: Introduction to Graphical Modelling Finkelstein and Levin: Statistics for Lawyers Flury: A First Course in Multivariate Statistics Jobson: Applied Multivariate Data Analysis, Volume I: Regression and Experimental Design Jobson: Applied Multivariate Data Analysis, Volume II: Categorical and Multivariate Methods Kalbfleisch: Probability and Statistical Inference, Volume I: Probability, Second Edition Kalbfleisch: Probability and Statistical Inference, Volume II: Statistical Inference, Second Edition Karr: Probability Keyfitz: Applied Mathematical Demography, Second Edition Kiefer: Introduction to Statistical Inference Kokoska and Nevison: Statistical Tables and Formulae Kulkarni: Modeling, Analysis, Design, and Control of Stochastic Systems Lehmann: Elements of Large-Sample Theory Lehmann: Testing Statistical Hypotheses, Second Edition Lehmann and Casella: Theory of Point Estimation, Second Edition Lindman: Analysis of Variance in Experimental Design Lindsey: Applying Generalized Linear Models Madansky: Prescriptions for Working Statisticians McPherson: Statistics in Scientific Investigation: Its Basis, Application, and Interpretation Mueller: Basic Principles of Structural Equation Modeling Nguyen and Rogers: Fundamentals of Mathematical Statistics: Volume I: Probability for Statistics Nguyen and Rogers: Fundamentals of Mathematical Statistics: Volume II: Statistical Inference
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Christian P. Robert
George Casella
Monte Carlo Statistical Methods With 65 Figures
,
Springer
Christian P. Robert
George Casella
CREST-INSEE Laboratoire de Statistique 75675 Paris Cedex 14 France
Biometrics Unit Comell University Ithaca, NY 14853-7801 USA
Dept. de Mathematique UFR des Sciences Universite de Rouen 76821 Mont Saint Aignan cedex France
Editorial Board
George Casella
Stephen Fienberg
Ingram Olkin
Biometrics Unit Cornell University Ithaca, NY 14853-7801 USA
Department of Statistics Carnegie Mellon University Pittsburgh, PA 15213 USA
Department of Statistics Stanford University Stanford, CA 94305 USA
Library of Congre
