mv_emloop: Multivariate expectation-maximization

In benja0x40/Tightrope: ChIP-seq normalization according to background reads density

Description

Multivariate expectation-maximization

Usage

mv_emloop(x, theta, p_fun = mv_pdf, mle_fun = mv_mle, max_iter = 100)

Arguments

x	numeric matrix representing multivariate data where rows = observations and columns = samples or conditions.
theta	list of multivariate distribution parameters
p_fun	probability density function (default = mv_pdf)
mle_fun	maximum likelyhood estimator function (default = mv_mle)
max_iter	maximum number of iterations (default = 100)

Value

mv_emloop returns a list with the following elements:

theta	list of multivariate distribution parameters
p	vector of probabilities

See Also

mv_maximization, mv_expectation, mv_gmm

benja0x40/Tightrope documentation built on May 24, 2019, 1:35 a.m.