archived R/PoisAR1_GL.R

In jlivsey/countsFun:

# PoisAR1_GL = function(CountDist,MargParm,ARParm, n, nsim, no_cores) {
#
#   # PURPOSE: Wrapper that performs simulation and produces Poisson AR(1) Gaussian likelihood
#   # estimates for revised Figure 3 (see aarxiv)
#   #
#   #
#   # AUTHORS: Stefanos Kechagias, James Livsey, Vladas Pipiras
#   #
#   # DATE:    April 2020
#   #
#   # R version 3.6.3
#
#
# # ---- setup parameters for Poisson(lam)-AR(1) series ----
# initial.param = c(MargParm, ARParm)         # Initial PArameters
#
# # Generate all the data and save in a list
# l <- list()
# for(r in 1:nsim){
#   set.seed(r)
#   l[[r]] = sim_pois_ar(n, ARParm, MargParm )
# }
#
# # initiate and register the cluster
# cl <- makeCluster(no_cores)
# registerDoParallel(cl)
#
# # fit the gaussian log likelihood using foreach
# all = foreach(index = 1:nsim,
#               .combine = rbind,
#               .packages = c("MASS", "countsFun")) %dopar%
#   FitGaussianLik(initial.param, l[[index]])
#
# stopCluster(cl)
#
# # Prepare results for the plot.
# df = data.frame(matrix(ncol = 8, nrow = nsim))
#
# #Create columns lam.est, phi.est, estim.method, n, phi, phi.se, lam, lam.se
# names(df) = c('lam.est', 'phi.est', 'estim.method', 'n', 'phi.true', 'phi.se', 'lam.true', 'lam.se')
#
# df[,1:2] = all[,1:2]
# df[,3] = 'gaussianLik'
# df[,4] = n
# df[,5] = ARParm
# df[,6] = all[,4]
# df[,7] = MargParm
# df[,8] = all[,3]
#
# return(df)
# }
#
#
#