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##############################################
## R sources for reproducing the results in ##
## Marko Nagode: ##
## Finite Mixture Modeling via REBMIX ##
##############################################
options(prompt = "> ", continue = "+ ", width = 70,
useFancyQuotes = FALSE, digits = 3)
###################
## Preliminaries ##
###################
# load package.
library(rebmix)
##################################
## Multivariate normal datasets ##
##################################
# Generate multivariate normal datasets.
n <- c(75, 100, 125, 150, 175)
Theta <- new("RNGMIX.Theta", c = 5, pdf = rep("normal", 4))
a.theta1(Theta, 1) <- c(10, 12, 10, 12)
a.theta1(Theta, 2) <- c(8.5, 10.5, 8.5, 10.5)
a.theta1(Theta, 3) <- c(12, 14, 12, 14)
a.theta1(Theta, 4) <- c(13, 15, 7, 9)
a.theta1(Theta, 5) <- c(7, 9, 13, 15)
a.theta2(Theta, 1) <- c(1, 1, 1, 1)
a.theta2(Theta, 2) <- c(1, 1, 1, 1)
a.theta2(Theta, 3) <- c(1, 1, 1, 1)
a.theta2(Theta, 4) <- c(2, 2, 2, 2)
a.theta2(Theta, 5) <- c(3, 3, 3, 3)
normal <- RNGMIX(Dataset = paste("normal_", 1:100, sep = ""), n = n, Theta = a.Theta(Theta))
# Estimate number of components, component weights and component parameters.
Sturges <- as.integer(1 + log2(sum(n))) # Minimum v follows the Sturges rule.
Log10 <- as.integer(10 * log10(sum(n))) # Maximum v follows the Log10 rule.
normalest <- REBMIX(Dataset = a.Dataset(normal), Preprocessing = "histogram",
K = Sturges:Log10, Criterion = "BIC", pdf = rep("normal", 4))
c <- a.summary(normalest, "c")
IC <- a.summary(normalest, "IC")
summary(c)
summary(IC, digits = 5)
format(length(c[c == 5]) / length(c))
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