-optimBeta <- function(N, n, K, p, beta, b, link, ncores)
+optimBeta <- function(N, n, p, beta, b, link, ncores)
{
library(morpheus)
res <- multiRun(
- list(n=n, p=p, beta=beta, b=b, K=K, link=link),
+ list(n=n, p=p, beta=beta, b=b, link=link),
list(
# morpheus
function(fargs) {
library(morpheus)
- K <- fargs$K
+ K <- ncol(fargs$beta)
M <- computeMoments(fargs$X, fargs$Y)
mu <- computeMu(fargs$X, fargs$Y, list(K=K, M=M))
op <- optimParams(fargs$X, fargs$Y, K, fargs$link, M)
# function(fargs) {
# library(flexmix)
# source("../patch_Bettina/FLXMRglm.R")
-# K <- fargs$K
+# K <- ncol(fargs$beta)
# dat <- as.data.frame( cbind(fargs$Y,fargs$X) )
# res2 <- NULL
# tryCatch({
res
}
-#model = binomial; default values:
+# Default values:
link = "logit"
N <- 10
d <- 2
}
if (d == 2) {
- K <- 2
p <- .5
b <- c(-.2, .5)
- beta <- matrix( c(1,-2, 3,1), ncol=K )
+ beta <- matrix( c(1,-2, 3,1), ncol=2 )
} else if (d == 5) {
- K <- 2
p <- .5
b <- c(-.2, .5)
- beta <- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=K )
+ beta <- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=2 )
} else if (d == 10) {
- K <- 3
p <- c(.3, .3)
b <- c(-.2, 0, .5)
- beta <- matrix( c(1,2,-1,0,3,4,-1,-3,0,2, 2,-3,0,1,0,-1,-4,3,2,0, -1,1,3,-1,0,0,2,0,1,-2), ncol=K )
-} else if (d == 20) {
- K <- 3
- p <- c(.3, .3)
- b <- c(-.2, 0, .5)
- beta <- matrix( c(1,2,-1,0,3,4,-1,-3,0,2,2,-3,0,1,0,-1,-4,3,2,0, -1,1,3,-1,0,0,2,0,1,-2,1,2,-1,0,3,4,-1,-3,0,2, 2,-3,0,1,0,-1,-4,3,2,0,1,1,2,2,-2,-2,3,1,0,0), ncol=K )
+ beta <- matrix( c(1,2,-1,0,3,4,-1,-3,0,2, 2,-3,0,1,0,-1,-4,3,2,0, -1,1,3,-1,0,0,2,0,1,-2), ncol=3 )
}
-mr <- optimBeta(N, n, K, p, beta, b, link, ncores)
+mr <- optimBeta(N, n, p, beta, b, link, ncores)
mr_params <- list("N"=N, "nc"=ncores, "n"=n, "K"=K, "d"=d, "link"=link,
"p"=c(p,1-sum(p)), "beta"=beta, "b"=b)
library(morpheus)
-testMultistart <- function(N, n, d, K, p, beta, b, link, nstart, ncores)
+testMultistart <- function(N, n, p, beta, b, link, nstart, ncores)
{
res <- multiRun(
- list(n=n,p=p,beta=beta,b=b,optargs=list(K=K,d=d,link=link,nstart=nstart)),
+ list(n=n, p=p, beta=beta, b=b, link=link, nstart=nstart),
list(
function(fargs) {
# 1 start
library(morpheus)
- K <- fargs$optargs$K
- op <- optimParams(K, fargs$optargs$link, fargs$optargs)
+ K <- ncol(fargs$beta)
+ op <- optimParams(fargs$X, fargs$Y, K, fargs$link, fargs$M)
x_init <- list(p=rep(1/K,K-1), beta=fargs$mu, b=rep(0,K))
res2 <- NULL
tryCatch({
function(fargs) {
# B starts
library(morpheus)
- K <- fargs$optargs$K
- d <- fargs$optargs$d
- op <- optimParams(K, fargs$optargs$link, fargs$optargs)
+ K <- ncol(fargs$beta)
+ d <- nrow(fargs$beta)
+ op <- optimParams(fargs$X, fargs$Y, K, fargs$link, fargs$M)
best_val <- Inf
best_par <- list()
- for (i in 1:fargs$optargs$nstart)
+ for (i in 1:fargs$nstart)
{
#x_init <- list(p=rep(1/K,K-1), beta=i*fargs$mu, b=rep(0,K))
M <- matrix(rnorm(d*K), nrow=d, ncol=K)
),
prepareArgs = function(fargs, index) {
library(morpheus)
- io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$optargs$link)
- fargs$optargs$M <- computeMoments(io$X, io$Y)
- mu <- computeMu(io$X, io$Y, fargs$optargs)
+ io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$link)
+ fargs$M <- computeMoments(io$X, io$Y)
+ mu <- computeMu(io$X, io$Y, list(M=fargs$M))
fargs$mu <- mu
+ fargs$X <- io$X
+ fargs$Y <- io$Y
fargs
}, N=N, ncores=ncores, verbose=TRUE)
for (i in 1:2)
res
}
-#model = binomial
-K <- 2
-p <- .5
-b <- c(-.2, .5)
# Default values:
link = "logit"
N <- 10
-d <- 2
n <- 1e4
ncores <- 1
nstart <- 3 #nstart-1 random starting points for each MC run
}
}
}
-betas <- list(
- matrix( c(1,-2, 3,1), ncol=K ), #d=2
- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=K ), #d=5
- matrix( c(1,2,-1,0,3,4,-1,-3,0,2, 2,-3,0,1,0,-1,-4,3,2,0), ncol=K ) ) #d=10
-beta <- betas[[ ifelse( d==2, 1, ifelse(d==5,2,3) ) ]]
-mr <- testMultistart(N, n, d, K, p, beta, b, link, nstart, ncores)
-mr_params <- list("N"=N, "nc"=ncores, "n"=n, "K"=K, "d"=d, "link"=link,
+if (d == 2) {
+ p <- .5
+ b <- c(-.2, .5)
+ beta <- matrix( c(1,-2, 3,1), ncol=2 )
+} else if (d == 5) {
+ p <- .5
+ b <- c(-.2, .5)
+ beta <- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=2 )
+} else if (d == 10) {
+ 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=3 )
+}
+
+mr <- testMultistart(N, n, p, beta, b, link, nstart, ncores)
+mr_params <- list("N"=N, "nc"=ncores, "n"=n, "link"=link,
"p"=c(p,1-sum(p)), "beta"=beta, "b"=b, "nstart"=nstart)
save("mr", "mr_params", file=paste("res_",n,"_",d,"_",link,"_",nstart,".RData",sep=""))