cauchyerrorpost

vector of parameter values of M and log S

theta

vector containing sample of observations

data

Computes the log posterior density of (M,log S) when
a sample is taken from a Cauchy density with location M and scale S and a uniform
prior distribution is taken on (M, log S)

models

A collection of functions helpful in learning the basic tenets of Bayesian statistical inference.  It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions.  It contains MCMC algorithms for summarizing posterior distributions defined by the user.  It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

cauchyerrorpost: Log posterior of median and log scale parameters for Cauchy sampling

Description

Usage

Arguments

Value

Examples