+optimBeta <- function(N, n, K, p, beta, b, link, ncores)
+{
+ library(morpheus)
+ res <- multiRun(
+ list(n=n,p=p,beta=beta,b=b,optargs=list(K=K,link=link)),
+ list(
+ # morpheus
+ function(fargs) {
+ library(morpheus)
+ K <- fargs$optargs$K
+ M <- computeMoments(fargs$X, fargs$Y)
+ fargs$optargs$M <- M
+ mu <- computeMu(fargs$X, fargs$Y, fargs$optargs)
+ op <- optimParams(K,link,fargs$optargs)
+ x_init <- list(p=rep(1/K,K-1), beta=mu, b=rep(0,K))
+ do.call(rbind, op$run(x_init))
+ },
+ # flexmix
+ function(fargs) {
+ library(flexmix)
+ source("../patch_Bettina/FLXMRglm.R")
+ K <- fargs$optargs$K
+ dat <- as.data.frame( cbind(fargs$Y,fargs$X) )
+ fm <- flexmix( cbind(V1, 1-V1) ~ .-V1, data=dat, k=K,
+ model = FLXMRglm(family = binomial(link = link)) )
+ p <- mean(fm@posterior[["scaled"]][,1])
+ out <- refit(fm)
+ beta_b <- sapply( seq_len(K), function(i) {
+ as.double( out@components[[1]][[i]][,1] )
+ } )
+ rbind(p, beta_b[2:nrow(beta_b),], beta_b[1,])
+ } ),
+ prepareArgs = function(fargs, index) {
+ library(morpheus)
+ io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$optargs$link)
+ fargs$X = io$X
+ fargs$Y = io$Y
+ fargs$optargs$K = ncol(fargs$beta)
+ fargs$optargs$M = computeMoments(io$X,io$Y)
+ fargs
+ }, N=N, ncores=ncores, verbose=TRUE)
+ p <- c(p, 1-sum(p))
+ for (i in 1:2)
+ res[[i]] <- alignMatrices(res[[i]], ref=rbind(p,beta,b), ls_mode="exact")
+ res
+}
+
+#model = binomial; default values:
+link = "logit"
+N <- 10
+d <- 2
+n <- 1e4
+ncores <- 1
+
+cmd_args <- commandArgs()
+for (arg in cmd_args)
+{
+ if (substr(arg,1,1)!='-') {
+ spl <- strsplit(arg,'=')[[1]]
+ if (spl[1] == "nc") {
+ ncores <- as.integer(spl[2])
+ } else if (spl[1] == "N") {
+ N <- as.integer(spl[2])
+ } else if (spl[1] == "n") {
+ n <- as.integer(spl[2])
+ } else if (spl[1] == "d") {
+ d <- as.integer(spl[2])
+ } else if (spl[1] == "link") {
+ link <- spl[2]
+ }
+ }
+}
+
+if (d == 2) {
+ K <- 2
+ p <- .5
+ b <- c(-.2, .5)
+ beta <- matrix( c(1,-2, 3,1), ncol=K )
+} else if (d == 5) {
+ K <- 2
+ p <- .5
+ b <- c(-.2, .5)
+ beta <- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=K )
+} else if (d == 10) {
+ K <- 3
+ p <- c(.3, .3)
+ b <- c(-.2, 0, .5)
+ beta <- matrix( c(1,2,-1,0,3,4,-1,-3,0,2, 2,-3,0,1,0,-1,-4,3,2,0, -1,1,3,-1,0,0,2,0,1,-2), ncol=K )
+} else if (d == 20) {
+ K <- 3
+ p <- c(.3, .3)
+ b <- c(-.2, 0, .5)
+ beta <- matrix( c(1,2,-1,0,3,4,-1,-3,0,2,2,-3,0,1,0,-1,-4,3,2,0, -1,1,3,-1,0,0,2,0,1,-2,1,2,-1,0,3,4,-1,-3,0,2, 2,-3,0,1,0,-1,-4,3,2,0,1,1,2,2,-2,-2,3,1,0,0), ncol=K )
+}
+
+mr <- optimBeta(N, n, K, p, beta, b, link, ncores)
+mr_params <- list("N"=N, "n"=n, "K"=K, "d"=d, "link"=link,
+ "p"=c(p,1-sum(p)), "beta"=beta, "b"=b)
+
+save("mr", "mr_params", file=paste("multirun_",d,"_",link,".RData",sep=""))