R: Independence Metropolis independence chain of a posterior...

indepmetrop {LearnBayes} | R Documentation

## Independence Metropolis independence chain of a posterior distribution

### Description

Simulates iterates of an independence Metropolis chain with a normal proposal density for an arbitrary real-valued posterior density defined by the user

### Usage

    indepmetrop(logpost,proposal,start,m,...)

### Arguments

`logpost` | function defining the log posterior density
`proposal` | a list containing mu, an estimated mean and var, an estimated variance-covariance matrix, of the normal proposal density
`start` | vector containing the starting value of the parameter
`m` | the number of iterations of the chain
`...` | data that is used in the function logpost

### Value

`par` | a matrix of simulated values where each row corresponds to a value of the vector parameter
`accept` | the acceptance rate of the algorithm

### Author(s)

Jim Albert

### Examples

    data=c(6,2,3,10)
    proposal=list(mu=array(c(2.3,-.1),c(2,1)),var=diag(c(1,1)))
    start=array(c(0,0),c(1,2))
    m=1000
    fit=indepmetrop(logctablepost,proposal,start,m,data)

[Package LearnBayes version 2.15 Index]