Nothing
library(MixfMRI, quietly = TRUE)
source("00-set_condition.r")
### Test 2d data
da <- eval(parse(text = paste(case, sep = "")))
id <- !is.na(da)
PV.gbd <- da[id]
id.loc <- which(id, arr.ind = TRUE)
X.gbd <- t(t(id.loc) / dim(da))
### Load results
ret <- NULL
ret.PARAM <- NULL
for(i.k in K.min:K.max){
ret.PARAM[[i.k]] <- list()
class(ret.PARAM[[i.k]]) <- "try-error"
fn.in <- paste("./output/ret.", case, ".tp.K_", i.k, ".rda", sep = "")
if(file.exists(fn.in)){
load(fn.in)
ret.PARAM[[i.k]] <- PARAM
ret <- rbind(ret, c(i.k, ret.PARAM[[i.k]]$param$logL,
ret.PARAM[[i.k]]$aic, ret.PARAM[[i.k]]$bic,
ret.PARAM[[i.k]]$icl.bic))
}
}
colnames(ret) <- c("K", "logL", "AIC", "BIC", "ICL-BIC")
print(ret)
# cat("\nLRT: H0: alpha = beta = 1 v.s. Ha: alpha < 1, beta > 1\n")
# for(i.k in K.min:K.max){
# if(length(ret.PARAM) >= i.k &&
# class(ret.PARAM[[i.k]]) != "try-error"){
# ret <- lrt(PV.gbd, ret.PARAM[[i.k]]$class, ret.PARAM[[i.k]]$param$K)
# cat("K = ", i.k, "\n", sep = "")
# print(ret)
# }
# }
cat("\nLRT2: H0: mean >= 0.05 v.s. Ha: mean < 0.05\n")
for(i.k in K.min:K.max){
if(length(ret.PARAM) >= i.k &&
class(ret.PARAM[[i.k]]) != "try-error"){
ret <- lrt2(PV.gbd, ret.PARAM[[i.k]]$class, ret.PARAM[[i.k]]$param$K)
cat("K = ", i.k, "\n", sep = "")
print(ret)
}
}
fn.out <- paste("./output/ret.", case, ".tp.rda", sep = "")
save(ret.PARAM, file = fn.out)
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