-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 <- c( rep(1/K,K-1), as.double(mu), 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=""))