Bayesian Methods for Statistical Analysis by Borek Puza Publisher: ANU Press 2015ISBN-13: 9781921934254Number of pages: 697 Description:A book on statistical methods for analysing a wide variety of data. Topics: bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models,...
Bayesian Methods: An Analysis for Statisticians and Interdisciplinary Researchers - Leonard, Hsu - 1999 () Citation Context ...lysis are potentially overcome by using what is known as the Laplacian approximation to the marginal probability (see, for example, Carlin & Louis, 2000, pp.122–129; ...
Bayesian methods have been used extensively in statistical decision theory (seestatistics: Decision analysis). In thiscontext, Bayes’s theorem provides a mechanism for combining a prior probability distribution for the states of nature with sample information to provide a revised (posterior) probability...
This paper presents a conceptual introduction to Bayesian methods, without the use of equations. It would be a good initial piece to introduce to students new to the topic, or those who are from more of a nontechnical background. It is written for developmental psychologists, but students and...
formally incorporated into statistical evaluation, Bayesian methods explicitly quantify the otherwise implicit influ- ence of clinical judgment and prior beliefs on the interpretation of trial results. 在临床试验的统计分析中,常规的频率主...
“The book is a good introductory treatment of methods of Bayes analysis. It should especially appeal to the reader who has had some statistical courses in estimation and modeling, and wants to understand the Bayesian interpretation of those methods. Also, readers who are primarily interested in ...
Because Bayesian statistical methods can be applied to any data, regardless of the type of cognitive model (Bayesian or otherwise) that motivated the data collection, Bayesian methods for data analysis will continue to be appropriate even if Bayesian models of mind lose their appeal. View article ...
Variables initially selected for this analysis were those which had a “p” value less or equal 0,150, under the bivariate analysis. P...Bergerud W. A. and Reed W. J. (1998) Bayesian Statistical Methods. In: Statistical Methods for Adaptive Management Studies (eds Sit V. and Taylor B...
MCMC methods Adaptive Metropolis–Hastings (MH) Adaptive MH with Gibbs updates—hybrid Full Gibbs sampling for some models Graphical tools to check MCMC convergence Posterior summaries: means, medians, SDs, MCSEs, CrIs Hypothesis testing: interval, model posterior probabilities ...
By contrast,Bayesian analysisprovides coherent methods for computing the power and replication probability. Bayesian power analysis uses the posterior distribution to sample many different plausible parameter values, and for each parameter value generates plausible data that simulate a repetition of the exper...