Fundraising September 15, 2024 – October 1, 2024 About fundraising

Statistical decision theory and Bayesian analysis

Main
Mathematics
Statistical decision theory and...

Statistical decision theory and Bayesian analysis

Berger, James O

0 / 0

How much do you like this book?

What’s the quality of the file?

Download the book for quality assessment

What’s the quality of the downloaded files?

Categories:

Year:

2011

Edition:

2nd ed

Publisher:

Springer

Language:

english

ISBN 10:

147574286X

ISBN 13:

9781475742862

Series:

Springer series in statistics

File:

PDF, 53.41 MB

IPFS:

,

english, 2011

Read Online

Conversion to is in progress

Conversion to is failed

You may be interested in

Jayanta K. Ghosh, Mohan Delampady, Tapas Samanta — An Introduction to Bayesian Analysis: Theory and Methods

Peter Bickel, Kjell Doksum — Mathematical Statistics Basic Ideas and Selected Topics Volume II

James O.Berger — 统计决策理论与贝叶斯分析

Berger — Statistical Decision Theory and Bayesian Analysis

Boes, Duane C.;Graybill, Franklin A.;Mood, Alexander McFarlane — Introduction to the theory of statistics

Thomas S. Ferguson — Mathematical Statistics: A Decision Theoretic Approach

Harold Jeffreys — Theory of probability, 3rd Edition

Devinderjit Sivia, John Skilling — Data Analysis: A Bayesian Tutorial

Jose M. Bernardo, M. J. Bayarri, James O. Berger, A. P. Dawid, David Heckerman, Adrian F. M. Smith, Mike West — Bayesian Statistics 9

Paul Damien, Petros Dellaportas, Nicholas G. Polson, David A. Stephens (eds.) — Bayesian Theory and Applications

George E. P. Box, George C. Tiao — Bayesian Inference in Statistical Analysis (Wiley Classics Library)

John Winsor Pratt, Howard Raïffa, Robert Schlaifer — Introduction to statistical decision theory

Anthony O'Hagan — The Advanced Theory of Statistics, Vol. 2B: Bayesian Inference

Jim Albert (auth.) — Bayesian Computation With R

Christian Robert; George Casella — Monte Carlo Statistical Methods

James E. Gentle — Elements of Computational Statistics

W.N. Venables, B.D. Ripley — Modern applied statistics with S

Peter D. Hoff — A First Course in Bayesian Statistical Methods

Jun S. Liu — Monte Carlo Strategies in Scientific Computing

James O. Berger — Statistical decision theory and bayesian analysis

E.L. Lehmann, George Casella — Theory of Point Estimation

Bradley Efron, R.J. Tibshirani — An Introduction to the Bootstrap (Chapman & Hall CRC Monographs on Statistics & Applied Probability)

Brian J. Reich, Sujit K. Ghosh — Bayesian Statistical Methods

Vladimir N. Vapnik — Statistical Learning Theory

Arnold Zellner — An introduction to Bayesian inference in econometrics

S. James Press — Subjective and Objective Bayesian Statistics: Principles, Models, and Applications

Schlaifer, Robert; Raiffa, Howard — Applied statistical decision theory

José M. Bernardo, Adrian F. M. Smith — Bayesian Theory

Giovanni Parmigiani, Lurdes Inoue — Decision Theory: Principles and Approaches (Wiley Series in Probability and Statistics)

Geweke J. — Contemporary Bayesian Econometrics And Statistics

Leonard J. Savage — The Foundations of Statistics, Second Revised Edition

Brazzale A. R., Reid N., Davison A. C. — Applied Asymptotics: Case Studies in Small-Sample Statistics

Thomas A. Severini — Elements of distribution theory

Bradley Efron — Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction (Institute of Mathematical Statistics Monographs)

A. C. Davison, D. V. Hinkley — Bootstrap Methods and their Application

Jim Q. Smith — Bayesian Decision Analysis: Principles and Practice

Martin Peterson — An Introduction to Decision Theory

George Casella; Roger L. Berger — Statistical Inference

Dipak K. Dey, Sujit K. Ghosh, Bani K. Mallick — Generalized Linear Models: A Bayesian Perspective

Bradley Efron — The Jackknife, the Bootstrap, and Other Resampling Plans

Galen R. Shorack; Jon A. Wellner — Empirical Processes with Applications to Statistics

Peter Congdon — Applied Bayesian Modelling

Most frequently terms