reports/accuracy.R

   1 optimBeta <- function(N, n, p, beta, b, link, ncores)
   2 {
   3   library(morpheus)
   4   res <- multiRun(
   5     list(n=n, p=p, beta=beta, b=b, link=link),
   6     list(
   7       # morpheus
   8       function(fargs) {
   9         library(morpheus)
  10         K <- ncol(fargs$beta)
  11         M <- computeMoments(fargs$X, fargs$Y)
  12         mu <- computeMu(fargs$X, fargs$Y, list(K=K, M=M))
  13         op <- optimParams(fargs$X, fargs$Y, K, fargs$link, M)
  14         x_init <- list(p=rep(1/K,K-1), beta=mu, b=rep(0,K))
  15         res2 <- NULL
  16         tryCatch({
  17           res2 <- do.call(rbind, op$run(x_init))
  18         }, error = function(e) {})
  19         res2
  20       },
  21       # flexmix
  22       function(fargs) {
  23         library(flexmix)
  24         source("../patch_Bettina/FLXMRglm.R")
  25         K <- ncol(fargs$beta)
  26         dat <- as.data.frame( cbind(fargs$Y,fargs$X) )
  27         res2 <- NULL
  28         tryCatch({
  29           fm <- flexmix( cbind(V1, 1-V1) ~ .-V1, data=dat, k=K,
  30             model = FLXMRglm(family = binomial(link = link)) )
  31           p <- mean(fm@posterior[["scaled"]][,1])
  32           out <- refit(fm)
  33           beta_b <- sapply( seq_len(K), function(i) {
  34             as.double( out@components[[1]][[i]][,1] )
  35           } )
  36           res2 <- rbind(p, beta_b[2:nrow(beta_b),], beta_b[1,])
  37         }, error = function(e) {
  38           res2 <- NA
  39         })
  40         res2
  41       }
  42     ),
  43     prepareArgs = function(fargs, index) {
  44       library(morpheus)
  45       io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$link)
  46       fargs$X = io$X
  47       fargs$Y = io$Y
  48       fargs
  49     }, N=N, ncores=ncores, verbose=TRUE)
  50   p <- c(p, 1-sum(p))
  51   for (i in 1:length(res)) {
  52     for (j in N:1) {
  53       if (is.null(res[[i]][[j]]) || is.na(res[[i]][[j]]))
  54         res[[i]][[j]] <- NULL
  55     }
  56     print(paste("Count valid runs for ",i," = ",length(res[[i]]),sep=""))
  57     res[[i]] <- alignMatrices(res[[i]], ref=rbind(p,beta,b), ls_mode="exact")
  58   }
  59   res
  60 }
  61
  62 # Default values:
  63 link = "logit"
  64 N <- 10
  65 d <- 2
  66 n <- 1e4
  67 ncores <- 1
  68
  69 cmd_args <- commandArgs()
  70 for (arg in cmd_args)
  71 {
  72   if (substr(arg,1,1)!='-') {
  73     spl <- strsplit(arg,'=')[[1]]
  74     if (spl[1] == "nc") {
  75       ncores <- as.integer(spl[2])
  76     } else if (spl[1] == "N") {
  77       N <- as.integer(spl[2])
  78     } else if (spl[1] == "n") {
  79       n <- as.integer(spl[2])
  80     } else if (spl[1] == "d") {
  81       d <- as.integer(spl[2])
  82     } else if (spl[1] == "link") {
  83       link <- spl[2]
  84     }
  85   }
  86 }
  87
  88 if (d == 2) {
  89   p <- .5
  90   b <- c(-.2, .5)
  91   beta <- matrix( c(1,-2, 3,1), ncol=2 )
  92 } else if (d == 5) {
  93   p <- .5
  94   b <- c(-.2, .5)
  95   beta <- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=2 )
  96 } else if (d == 10) {
  97   p <- c(.3, .3)
  98   b <- c(-.2, 0, .5)
  99   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 )
 100 }
 101
 102 mr <- optimBeta(N, n, p, beta, b, link, ncores)
 103 mr_params <- list("N"=N, "nc"=ncores, "n"=n, "link"=link,
 104   "p"=c(p,1-sum(p)), "beta"=beta, "b"=b)
 105
 106 save("mr", "mr_params", file=paste("res_",n,"_",d,"_",link,".RData",sep=""))