plotexpRMM: Plot sequences from the EM algorithm for censored mixture of...

In mixtools: Tools for Analyzing Finite Mixture Models

Plot sequences from the EM algorithm for censored mixture of exponentials

Description

Function for plotting sequences of estimates along iterations, from an object returned by the expRMM_EM, an EM algorithm for mixture of exponential distributions with randomly right censored data (see reference below).

Usage

  plotexpRMM(a, title=NULL, rowstyle=TRUE, subtitle=NULL, ...)

Arguments

a	An object returned by expRMM_EM.
title	The title of the plot, set to some default value if NULL.
rowstyle	Window organization, for plots in rows (the default) or columns.
subtitle	A subtitle for the plot, set to some default value if NULL.
...	Other parameters (such as lwd) passed to plot, lines, and legend commands.

Value

The plot returned

Author(s)

Didier Chauveau

References

• Bordes, L., and Chauveau, D. (2016), Stochastic EM algorithms for parametric and semiparametric mixture models for right-censored lifetime data, Computational Statistics, Volume 31, Issue 4, pages 1513-1538. https://link.springer.com/article/10.1007/s00180-016-0661-7

See Also

Related functions: expRMM_EM, summary.mixEM, plot.mixEM.

Other models and algorithms for censored lifetime data (name convention is model_algorithm): weibullRMM_SEM, spRMM_SEM.

Examples

n=300 # sample size
m=2   # number of mixture components
lambda <- c(1/3,1-1/3); rate <- c(1,1/10) # mixture parameters
set.seed(1234)
x <- rexpmix(n, lambda, rate) # iid ~ exponential mixture
cs=runif(n,0,max(x)) # Censoring (uniform) and incomplete data
t <- apply(cbind(x,cs),1,min) # observed or censored data
d <- 1*(x <= cs)              # censoring indicator

###### EM for RMM, exponential lifetimes
l0 <- rep(1/m,m); r0 <- c(1, 0.5) # "arbitrary" initial values
a <- expRMM_EM(t, d, lambda=l0, rate=r0, k = m)
summary(a)             # EM estimates etc
plotexpRMM(a, lwd=2) # plot of EM sequences

mixtools documentation built on Dec. 5, 2022, 5:23 p.m.