controlmcmcSDA: control.mcmcSDA

In olatunjijohnson/SDALGCP: Spatially Discrete Approximation to Log-Gaussian Cox Processes for Aggregated Disease Count Data

Description

This function helps to define the number of iteration, burn-in, thining, and the tunning parameters of the adaptive MALA

Usage

controlmcmcSDA(n.sim, burnin, thin, h, c1.h, c2.h)

Arguments

n.sim	the number of iteration
burnin	The number of burn-in
thin	the number of thining
h	tuning parameter of the proposal distribution used in the Langevin-Hastings MCMC algorithm (see Laplace.sampling); default is h=NULL and then set internally as 1.65/n(1/6), where n is the dimension of the random effect.
c1.h	value of c1 used in the adaptive scheme for h; default is c1.h=0.01. See also 'Details' in PrevMap package
c2.h	value of c2 used in the adaptive scheme for h; default is c2.h=1e-04. See also 'Details' in PrevMap package

Details

To be used as one of the arguments of SDALGCPMCML

Value

A list with processed arguments to be passed to the main function.

Author(s)

Olatunji O. Johnson [e-mail]

Emanuele Giorgi [e-mail]

Peter J. Diggle [e-mail]

See Also

control.mcmc.MCML

Examples

n <- 545
h <- 1.65/(n^(1/6))
control.mcmc <- controlmcmcSDA(n.sim = 10000, burnin = 2000,
thin= 8, h=h, c1.h = 0.01, c2.h = 1e-04)
str(control.mcmc)

olatunjijohnson/SDALGCP documentation built on March 20, 2021, 4:24 a.m.