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1d014a86 BA |
1 | optimBeta <- function(N, n, K, p, beta, b, link, ncores) |
2 | { | |
3 | library(morpheus) | |
4 | res <- multiRun( | |
5 | list(n=n,p=p,beta=beta,b=b,optargs=list(K=K,link=link)), | |
6 | list( | |
7 | # morpheus | |
8 | function(fargs) { | |
9 | library(morpheus) | |
10 | K <- fargs$optargs$K | |
11 | M <- computeMoments(fargs$X, fargs$Y) | |
12 | fargs$optargs$M <- M | |
13 | mu <- computeMu(fargs$X, fargs$Y, fargs$optargs) | |
14 | op <- optimParams(K,link,fargs$optargs) | |
15 | x_init <- list(p=rep(1/K,K-1), beta=mu, b=rep(0,K)) | |
16 | do.call(rbind, op$run(x_init)) | |
17 | }, | |
18 | # flexmix | |
19 | function(fargs) { | |
20 | library(flexmix) | |
21 | source("../patch_Bettina/FLXMRglm.R") | |
22 | K <- fargs$optargs$K | |
23 | dat <- as.data.frame( cbind(fargs$Y,fargs$X) ) | |
24 | fm <- flexmix( cbind(V1, 1-V1) ~ .-V1, data=dat, k=K, | |
25 | model = FLXMRglm(family = binomial(link = link)) ) | |
26 | p <- mean(fm@posterior[["scaled"]][,1]) | |
27 | out <- refit(fm) | |
28 | beta_b <- sapply( seq_len(K), function(i) { | |
29 | as.double( out@components[[1]][[i]][,1] ) | |
30 | } ) | |
31 | rbind(p, beta_b[2:nrow(beta_b),], beta_b[1,]) | |
32 | } ), | |
33 | prepareArgs = function(fargs, index) { | |
34 | library(morpheus) | |
35 | io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$optargs$link) | |
36 | fargs$X = io$X | |
37 | fargs$Y = io$Y | |
38 | fargs$optargs$K = ncol(fargs$beta) | |
39 | fargs$optargs$M = computeMoments(io$X,io$Y) | |
40 | fargs | |
41 | }, N=N, ncores=ncores, verbose=TRUE) | |
42 | p <- c(p, 1-sum(p)) | |
43 | for (i in 1:2) | |
44 | res[[i]] <- alignMatrices(res[[i]], ref=rbind(p,beta,b), ls_mode="exact") | |
45 | res | |
46 | } | |
47 | ||
48 | #model = binomial; default values: | |
49 | link = "logit" | |
50 | N <- 10 | |
51 | d <- 2 | |
52 | n <- 1e4 | |
53 | ncores <- 1 | |
54 | ||
55 | cmd_args <- commandArgs() | |
56 | for (arg in cmd_args) | |
57 | { | |
58 | if (substr(arg,1,1)!='-') { | |
59 | spl <- strsplit(arg,'=')[[1]] | |
60 | if (spl[1] == "nc") { | |
61 | ncores <- as.integer(spl[2]) | |
62 | } else if (spl[1] == "N") { | |
63 | N <- as.integer(spl[2]) | |
64 | } else if (spl[1] == "n") { | |
65 | n <- as.integer(spl[2]) | |
66 | } else if (spl[1] == "d") { | |
67 | d <- as.integer(spl[2]) | |
68 | } else if (spl[1] == "link") { | |
69 | link <- spl[2] | |
70 | } | |
71 | } | |
72 | } | |
73 | ||
74 | if (d == 2) { | |
75 | K <- 2 | |
76 | p <- .5 | |
77 | b <- c(-.2, .5) | |
78 | beta <- matrix( c(1,-2, 3,1), ncol=K ) | |
79 | } else if (d == 5) { | |
80 | K <- 2 | |
81 | p <- .5 | |
82 | b <- c(-.2, .5) | |
83 | beta <- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=K ) | |
84 | } else if (d == 10) { | |
85 | K <- 3 | |
86 | p <- c(.3, .3) | |
87 | b <- c(-.2, 0, .5) | |
88 | 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 ) | |
89 | } else if (d == 20) { | |
90 | K <- 3 | |
91 | p <- c(.3, .3) | |
92 | b <- c(-.2, 0, .5) | |
93 | 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 ) | |
94 | } | |
95 | ||
96 | mr <- optimBeta(N, n, K, p, beta, b, link, ncores) | |
97 | mr_params <- list("N"=N, "n"=n, "K"=K, "d"=d, "link"=link, | |
98 | "p"=c(p,1-sum(p)), "beta"=beta, "b"=b) | |
99 | ||
100 | save("mr", "mr_params", file=paste("multirun_",d,"_",link,".RData",sep="")) |