mnemh: Hierarchical mixture.

In mnem: Mixture Nested Effects Models

Description

This function does a hierarchical mixture. That means it uses the approximate BIC to check, if there are more than one component. It recursively splits the data if there is evidence for k > 1 components.

Usage

mnemh(data, k = 2, logtype = 2, getprobspars = list(), ...)

Arguments

data	data matrix either binary or log odds
k	number of maximal components for each hierarchy leaf
logtype	log type of the data
getprobspars	list of parameters for the getProbs function
...	additional parameters for the mnem function

Value

object of class mnem

Author(s)

Martin Pirkl

Examples

sim <- simData(Sgenes = 3, Egenes = 2, Nems = 2, mw = c(0.4,0.6))
data <- (sim$data - 0.5)/0.5
data <- data + rnorm(length(data), 0, 1)
result <- mnemh(data, starts = 1, k = 1)

mnem documentation built on Nov. 18, 2020, 2 a.m.