isinghm

This is the Metropolis-Hastings version of the original Gibbs algorithm
on the Ising model (Chapter 8). Its basic step only proposes changes of values at selected
pixels, avoiding the inefficient updates that do not modify the current value
of <code>x</code>.

random walk

Ising model

Metropolis-Hastings

Allows the reenactment of the R programs used in
the book Bayesian Essentials with R without further programming.
R code being available as well, they can be modified by the user
to conduct one's own simulations.
Marin J.-M. and Robert C. P. (2014) <doi:10.1007/978-1-4614-8687-9>.

JeanMichel Marin

bayess

Bayesian Essentials with R

isinghm function

<dl> <dt>niter</dt>
<dd>number of iterations of the algorithm</dd> <dt>n</dt>
<dd>number of rows in the grid</dd> <dt>m</dt>
<dd>number of columns in the grid</dd> <dt>beta</dt>
<dd>Ising parameter</dd></dl>

Arguments

Metropolis-Hastings for the Ising model — isinghm

<dl>

 <dt>niter</dt>
<dd>number of iterations of the algorithm</dd>

 <dt>n</dt>
<dd>number of rows in the grid</dd>

 <dt>m</dt>
<dd>number of columns in the grid</dd>

 <dt>beta</dt>
<dd>Ising parameter</dd>

</dl>

isinghm: Metropolis-Hastings for the Ising model

Description

Usage

Value

Arguments

See Also

Examples