em_group_fit: Compute the maximum likelihood estimates of an exponential...

In brentfagan/mixem: Exponential Mixture Model MLEs using the EM algorithm

Description

Compute the maximum likelihood estimates of an exponential mixture distribution and number of mixtures when the data is grouped.

Usage

em_group_fit(x_grp, boundaries = NULL, data_type, prec = 1e-08,
  prec2 = 1e-04, itermax = 100, rmax = 10)

Arguments

x_grp	Grouped data vector.
boundaries	Interval boundaries of the grouped data.
data_type	Three possible data_types are 'interval', 'cross tab', or 'tabular'
prec	Precision used for testing convergence of mle's as measured by squared difference of loglikelihood functions.
prec2	Estimated mixing proportions below prec2 will cause algorithm to stop.
itermax	Maximum number of EM algorithm iterations.
rmax	Maximum number of mixtures to find.

Value

A list of mixing proportions p and associated means mean.

brentfagan/mixem documentation built on May 8, 2019, 1:37 a.m.