| prepare.likfit.glsm {geoRglm} | R Documentation |
This function takes an output object from glsm.mcmc, and the corresponding data object of class
geodata, and prepares the
variables needed for the Monte Carlo maximum likelihood function
likfit.glsm.
prepare.likfit.glsm(mcmc.output, use.intensity = FALSE)
mcmc.output |
an output file from the function glsm.mcmc. |
use.intensity |
logical. If use.intensity = TRUE then the integration variable in the Monte Carlo approximation
will not be S but the intensity g_{lambda}^{-1}(S). The latter makes it possible to
use other link functions in likfit.glsm than the one used in mcmc.output.
Default is use.intensity = FALSE. |
An object containing the sample and the approximating density to be used in likfit.glsm.
Ole F. Christensen OleF.Christensen@agrsci.dk,
Paulo J. Ribeiro Jr. Paulo.Ribeiro@est.ufpr.br.
likfit.glsm for how to use the output from this function, and glsm.mcmc for
generating the object mcmc.output.
## Not run:
data(p50)
mcmc.4 <- mcmc.control(S.scale = 0.000035, n.iter = 1000)
kr4 <- list(family="poisson", cov.pars=c(1,1), beta=0)
condsim.4 <- glsm.mcmc(p50, mcmc.input = mcmc.4, model = kr4)
mcmcobj.4 <- prepare.likfit.glsm(condsim.4)
lik.4 <- likfit.glsm(mcmcobj.4, ini.phi = 10, fix.nugget.rel = TRUE)
lik.4.spherical.nugget <- likfit.glsm(mcmcobj.4, ini.phi = 5.59,
cov.model = "spherical", nugget.rel = 0.385)
## End(Not run)