sumising: Approximation by path sampling of the normalising constant...

In bayess: Bayesian Essentials with R

Approximation by path sampling of the normalising constant for the Ising model

Description

This function implements a path sampling approximation of the normalising constant of an Ising model with a four neighbour relation.

Usage

sumising(niter = 10^3, numb, beta)

Arguments

niter	number of iterations
numb	size of the square grid for the Ising model
beta	Ising model parameter

Value

returns a vector of 21 values for Z(\beta) corresponding to a regular sequence of \beta's between 0 and 2

See Also

isingibbs,isinghm

Examples

Z=seq(0,2,length=21)
for (i in 1:21)
  Z[i]=sumising(5,numb=24,beta=Z[i])
lrcst=approxfun(seq(0,2,length=21),Z)
plot(seq(0,2,length=21),Z,xlab="",ylab="")
curve(lrcst,0,2,add=TRUE)

bayess documentation built on May 29, 2024, 3:58 a.m.