2 morph <- function(fargs) {
4 M <- computeMoments(fargs$X, fargs$Y)
6 mu <- computeMu(fargs$X, fargs$Y, fargs$optargs)
9 op <- optimParams(K,link,fargs$optargs)
10 x_init <- list(p=rep(1/K,K-1), beta=mu, b=rep(0,K))
11 res2 <- do.call(rbind, op$run(x_init))
12 }, error = function(e) {
18 #model = binomial; default values:
29 beta <- matrix( c(1,-2, 3,1), ncol=K )
34 beta <- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=K )
39 beta <- matrix( c(1,2,-1,0,3,4,-1,-3,0,2, 2,-3,0,1,0,-1,-4,3,2,0, -1,1,3,-1,0,0,2,0,1,-2), ncol=K )
44 beta <- matrix( c(1,2,-1,0,3,4,-1,-3,0,2,2,-3,0,1,0,-1,-4,3,2,0, -1,1,3,-1,0,0,2,0,1,-2,1,2,-1,0,3,4,-1,-3,0,2, 2,-3,0,1,0,-1,-4,3,2,0,1,1,2,2,-2,-2,3,1,0,0), ncol=K )
47 fargs = list(n=n, p=p, beta=beta, b=b)
48 fargs$optargs = list(link=link)
50 io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$optargs$link)
53 fargs$optargs$K = ncol(fargs$beta)
54 fargs$optargs$M = computeMoments(io$X,io$Y)
58 save("res2", file="test.RData")