plotly_expRMM: 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 using plotly

Description

This is an updated function of plotexpRMM. For more technical details, please refer to plotexpRMM.

Usage

  plotly_expRMM(a , title = NULL , rowstyle = TRUE , subtitle=NULL,
  width = 2 , cex = 2 , col.comp = NULL,
  legend.text = NULL, legend.text.size = 15, legend.size = 15,
  title.x = 0.5, title.y = 0.95, title.size = 15,
  xlab.size = 15, xtick.size = 15, 
  ylab.size = 15, ytick.size = 15)

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.
width	Line width.
cex	Size of dots.
col.comp	Color of different components. Number of color specified needs to be consistent with number of components.
legend.text	Title of legend.
legend.text.size	Size of the legend title.
legend.size	Size of legend.
title.size	Size of the main title.
title.x	Horsizontal position of the main title.
title.y	Vertical posotion of the main title.
xlab.size	Size of the lable of X-axis.
xtick.size	Size of tick lables of X-axis.
ylab.size	Size of the lable of Y-axis.
ytick.size	Size of tick lables of Y-axis.

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, plotexpRMM.

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
plotly_expRMM(a , rowstyle = TRUE) # plot of EM sequences

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