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We illustrate the use of the Mathematica software system (programming language) for performing Bayesian calculations of the sort encountered in introductory presentations of ...
Abstract This talk will illustrate how I use Mathematica for Bayesian statistical and econometric analysis. Bayesian statistical techniques are numerically intensive ...
Bayesian Statistical Models provide statisticians and auditors with a set of powerful tools for attacking financial audit problems. Some of these statistical auditing ...
This article explains estimation of gene frequencies from a Bayesian viewpoint using prior information. How to obtain Bayes estimators and the highest posterior density ...
An analysis of the wildcatter's problem, a prototypical problem, is described.
In this paper we discuss the sample size problem for balanced one-way ANOVA under a posterior Bayesian formulation of the problem. Using the distribution theory of ...
We use a Bayesian approach to fitting a linear regression model to transformations of the natural parameter for the exponential class of distributions. The usual Bayesian ...
The paper presents a method for symbolic propagation of uncertainty in Bayesian discrete and continuous (normal) networks, using Mathematica. For the normal Bayesian networks ...
This book provides a clear exposition of the underlying concepts of Bayesian analysis, with large numbers of worked examples and problem sets. It also discusses numerical ...
This presentation illustrates Bayes' rule as the tool for inductive reasoning using the context of single parameter binary trials like: a head/tail coin toss, a pass/fail ...
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