devtools::load_all()
library(parallel)
RNGkind("L'Ecuyer-CMRG")
s_seed <- 999983
set.seed(s_seed)
v_n <- c(100, 200)
v_del <- c(0.2, 0.5, 1)
v_C <- c("fourier", "matern", "bspline");v_sige2 <- c(6.292991, 0.6890763, 0.001649281)
v_mu <- c(1)
k <- 100
dense_face <- mclapply(v_n, n_loop <- function(n){
mclapply(v_del, del_loop <- function(del){
mclapply(v_C, C_loop <- function(sigx){
mclapply(v_mu, mu_loop <- function(mu){
mclapply(1:k, sim_loop <- function(i){
sige = v_sige2[match(sigx, v_C)]
sim <- sim1(n, sige, del, m_avg = 20, sigx=sigx, mu=mu)
grid <- regular.grid()
fit1 = face::face.sparse(sim$data,argvals.new = grid)
return(list(data=sim$data, truemugrid=sim$truemugrid, truecovgrid=sim$truecovgrid,
muface = fit1$mu.new, Cface = fit1$Chat.new))
}, mc.cores = 8)
}, mc.cores = 1)
}, mc.cores = 1)
}, mc.cores = 1)
}, mc.cores = 1)
save(dense_face, file = "dense_face.RData")
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