expo.metrop

Simple Metropolis algorithm demonstration using a bivariate exponential target from Chapter 1 (pages 27-30).

Functions and datasets for Jeff Gill: "Bayesian Methods: A Social and Behavioral Sciences Approach". First, Second, and Third Edition. Published by Chapman and Hall/CRC (2002, 2007, 2014) <doi:10.1201/b17888>.

Jeff Gill

Functions and Datasets for "Bayesian Methods: A Social and
Behavioral Sciences Approach"

expo.metrop function

<dl><dt>m</dt>
<dd>number of iterations</dd>
<dt>x</dt>
<dd>starting point for the x vector</dd>
<dt>y</dt>
<dd>starting point for the y vector</dd>
<dt>L1</dt>
<dd>event intensity for the x dimension</dd>
<dt>L2</dt>
<dd>event intensity for the y dimension</dd>
<dt>L</dt>
<dd>shared event intensity</dd>
<dt>B</dt>
<dd>upper bound</dd></dl>

Arguments

Author

expo.metrop — expo.metrop

<dl>

<dt>m</dt>
<dd>number of iterations</dd>


<dt>x</dt>
<dd>starting point for the x vector</dd>


<dt>y</dt>
<dd>starting point for the y vector</dd>


<dt>L1</dt>
<dd>event intensity for the x dimension</dd>


<dt>L2</dt>
<dd>event intensity for the y dimension</dd>


<dt>L</dt>
<dd>shared event intensity</dd>


<dt>B</dt>
<dd>upper bound</dd>

</dl>

expo.metrop: expo.metrop

Description

Usage

Arguments

Author

Examples