--- /dev/null
+# flexmix optimization to get beta
+fmOptim <- function(X, Y, K, link)
+{
+ dat <- as.data.frame( cbind(Y,X) )
+ fm <- flexmix( cbind(Y, 1-Y) ~ .-Y, data=dat, k=K,
+ model = FLXMRglm(family = binomial(link = link)) )
+ p <- mean(fm@posterior[["scaled"]][,1])
+ out <- refit(fm)
+ beta_b <- sapply( seq_len(K), function(i) as.double( out@components[[1]][[i]][,1] ) )
+ list("p"=p, "beta"=beta_b[2:nrow(beta_b),], "b"=beta_b[1,])
+ NULL
+}
+
+# Our package optimization for beta (using mu as a starting point)
+ourOptim <- function(X, Y, K, link)
+{
+ M <- computeMoments(X, Y)
+ mu <- computeMu(X, Y, list(K=K,M=M))
+ x_init = c(1/2, as.double(mu), c(0,0))
+ optimParams(K, link, list(M=M))$run(x_init)
+ NULL
+}
+
+# Get timings for both methods with the same beta matrix
+getTimings <- function(link)
+{
+ timings <- list('fm'=matrix(0,nrow=10,ncol=7),'our'=matrix(0,nrow=10,ncol=7))
+ K <- 2
+ for (d in c(2,5,10))
+ {
+ beta <- matrix(runif(d*K,min=-5,max=5),ncol=K)
+ for (logn in 4:6)
+ {
+ n <- 10^logn
+ io <- generateSampleIO(n, rep(1/K,K-1), beta, runif(K), link)
+ timings[['fm']][d,logn] <- system.time(fmOptim(io$X,io$Y,K,link))[3]
+ timings[['our']][d,logn] <- system.time(ourOptim(io$X,io$Y,K,link))[3]
+ }
+ }
+ timings
+}
+
+#model = binomial
+link <- "logit"
+ncores <- 1
+N <- 100
+
+cmd_args <- commandArgs()
+for (arg in cmd_args)
+{
+ if (substr(arg,1,1)!='-')
+ {
+ spl <- strsplit(arg,'=')[[1]]
+ if (spl[1] == "link") {
+ link <- spl[2]
+ } else if (spl[1] == "nc") {
+ ncores <- as.integer(spl[2])
+ } else if (spl[1] == "N") {
+ N <- as.integer(spl[2])
+ }
+ }
+}
+
+library(morpheus)
+library(flexmix)
+source("../patch_Bettina/FLXMRglm.R")
+
+tm <-
+ if (ncores == 1) {
+ lapply(1:N, function(i) {
+ print(paste("Run",i))
+ getTimings(link)
+ })
+ } else {
+ library(parallel)
+ mclapply(1:N, function(i) {
+ print(paste("Run",i))
+ getTimings(link)
+ },
+ mc.preschedule=FALSE, mc.cores=ncores)
+ }
+tm_params <- list("link"=link, "N"=N, "nc"=ncores)
+
+save("tm", "tm_params", file="timings.RData")