tablecst {Geneclust} | R Documentation |
Computes the Potts-Dirichlet model normalization constants table by the method proposed by Sylvia Richardson and Peter J.Green in the article: "Hidden Markov Models and Disease Mapping"(JASA Dec 2002).
tablecst(pathtable, npopmax, coordinates, matngh, stepval = 0.02, nit.table = 20000, stepw.table = 10, burnin.table = 10000, plot=TRUE, write = FALSE)
pathtable |
Path to output file directory |
npopmax |
Initial number of populations |
coordinates |
Spatial coordinates of individuals. A matrix with 2 columns and one line per individual |
matngh |
The neighbourhood matrix with nindiv lines and nindiv columns. If matngh[i,j]=1 then the individuals i and j are neighbours. |
stepval |
Step of discretization of the interval [0,1]. The expected Potts system energy will be computed for each psi value of this discretized interval by MCMC simulations of Potts-Dirichlet configurations. By default, stepval=0.02. |
nit.table |
Number of MCMC iterations to generate Potts-Dirichlet configurations. |
stepw.table |
Number of MCMC iterations between two writing steps (if stepw.table =1, all
states are saved whereas if e.g. stepw.table =10 only each 10 iterations is saved) |
burnin.table |
Number of MCMC iterations to throw away to compute the expected Potts-Dirichlet system energy for each value of psi |
plot |
Logical: if plot=TRUE the Potts-Dirichlet model normalization constants are plotted for each value of psi (0,0.1,0.2,...,1) |
write |
Logical: if write=TRUE the table is written in a plain ascci file named table.txt |
A numerical vector (the table) with (10*1)+1 components. Each component is an approximation of the Potts-Dirichlet model normalization constant (at log scale) for each value of psi. We supposed that psi takes its values between 0 and 1 with a discretization step of 0.1.
All parameters processed by function tablecst
are
written in the directory specified by ‘pathtable’ as follows:
File ‘table.txt’ contains a numerical vector with 11 components. Each component is an approximation of the Potts-Dirichlet model normalization constant (at log scale) for each value of psi. We supposed that psi takes its values between 0 and 1 with a discretization step of 0.1.
(1/stepval)+1 repertories. Each one contains the outputs of a Gibbs sampler to generate data according to Potts-Dirichlet model for psi from 0 to 1 with a discretization step of 0.02.
Sophie Ancelet
Sylvia Richardson, Peter J.Green: "Hidden Markov Models and Disease Mapping"(JASA December 2002)
Function simpottsdir
#library(Geneclust) # Below is a sequence of R commands using Geneclust functions to compute # the Potts-Dirichlet model normalization constants table when we consider 100 individuals # organized in 2 populations. ## Not run: #To define a place for outputs system("mkdir ./tmpData/") pathtable <- "./tmpTable/" #To generate the coordinates of 100 individuals which are supposed #uniformly distributed in a rectangle coordinates<- matrix(runif(200,0,1),nrow=100,ncol=2) #To compute the neighbourhood matrix del<- deldir(x=coordinates[,1],y=coordinates[,2]) colngh<- del$delsgs[,5:6] pt<- nrow(colngh) matngh<- matrix(0,nrow=100, ncol=100) for(i in 1:pt){ matngh[colngh[i,1],colngh[i,2]]=1 matngh[colngh[i,2],colngh[i,1]]=1 } table<- tablecst (pathtable=pathtable, npopmax=2, coordinates=coordinates, matngh=matngh, stepval=0.02, nit.table=20000, stepw.table=10, burnin.table=10000, plot=TRUE, write=TRUE) ## go to file pathtable to read outputs ## End(Not run)