mvnMix: Multivariate Normal Mixture Models

View source: R/MVNSeq.r

mvnMixR Documentation

Multivariate Normal Mixture Models

Description

Fit multivariate Normal mixture models by EM.

Usage

mvnMix(
  y,
  cl,
  min.iters = 10,
  max.iters = 50,
  tol = 0.001,
  verbose = interactive()
)

gmvnMix(
  y,
  cl,
  gr,
  common.fractions = FALSE,
  min.iters = 10,
  max.iters = 50,
  tol = 0.001,
  verbose = interactive()
)

grmvnMix(
  y,
  cl,
  gr,
  common.fractions = FALSE,
  min.iters = 10,
  max.iters = 100,
  tol = 0.001,
  verbose = interactive()
)

Arguments

y

the sequence of observations

cl

an integer vector allocating observations to classes

min.iters

minimum number of EM iterations

max.iters

maximum number of EM iterations

tol

tolerance for the log likelihood

verbose

should the log likelihood be reported.

gr

an integer vector allocating observations to groups

common.fractions

should the mixing fractions be common across groups

Details

These functions fit K component multivariate Normal mixtures to sequences of observations. mvnMix fits a mixture model to a single sequence of observations. gmvnMix and grmvnMix fits separate mixture models to several groups (sequences) of observations. gmvnMix fits a mixture to each group so that each component has a different mean across groups, but a common covariance. grmvnMix constrains the means of the components to be Normally distributed across groups.

Value

the fitted model


SWotherspoon/MVNSeq documentation built on June 1, 2022, 10:49 p.m.