sdrni

Front-end to standard R random number seed setter, allowing retrospective replication

A program for Bayesian analysis of univariate normal mixtures with an unknown number
of components, following the approach of Richardson and Green (1997) <doi:10.1111/1467-9868.00095>.
This makes use of reversible jump Markov chain Monte Carlo methods that are capable of jumping
between the parameter sub-spaces corresponding to different numbers of components in the mixture.
A sample from the full joint distribution of all unknown variables is thereby generated,
and this can be used as a basis for a thorough presentation of many aspects of the posterior
distribution.

Peter Green

Nmix

Bayesian Inference on Univariate Normal Mixtures

sdrni function

<dl> <dt>seed</dt>
<dd>non-negative integer random number seed, often 0 for absolute re-initialisation as with <code>set.seed(NULL)</code></dd></dl>

Arguments

Author

Random number initialiser, allowing retrospective replication — sdrni

<dl>

 <dt>seed</dt>
<dd>non-negative integer random number seed, often 0 for absolute re-initialisation as with <code>set.seed(NULL)</code></dd>

</dl>

sdrni: Random number initialiser, allowing retrospective replication

Description

Usage

Value

Arguments

Author

Details

Examples