plotweibullRMM {mixtools} | R Documentation |
Plot sequences from the Stochastic EM algorithm for mixture of Weibull
Description
Function for plotting sequences of estimates along iterations, from an object returned by weibullRMM_SEM
, a Stochastic EM algorithm for mixture of Weibull
distributions with randomly right censored data (see reference below).
Usage
plotweibullRMM(a, title = NULL, rowstyle = TRUE, subtitle = NULL, ...)
Arguments
a |
An object returned by |
title |
The title of the plot, set to some default value if |
rowstyle |
Window organization, for plots in rows (the default) or columns. |
subtitle |
A subtitle for the plot, set to some default value if |
... |
Other parameters (such as |
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:
weibullRMM_SEM
, summary.mixEM
.
Other models and algorithms for censored lifetime data
(name convention is model_algorithm):
expRMM_EM
,
spRMM_SEM
.
Examples
n = 500 # sample size
m = 2 # nb components
lambda=c(0.4, 0.6)
shape <- c(0.5,5); scale <- c(1,20) # model parameters
set.seed(321)
x <- rweibullmix(n, lambda, shape, scale) # iid ~ weibull mixture
cs=runif(n,0,max(x)+10) # iid censoring times
t <- apply(cbind(x,cs),1,min) # censored observations
d <- 1*(x <= cs) # censoring indicator
## set arbitrary or "reasonable" (e.g., data-driven) initial values
l0 <- rep(1/m,m); sh0 <- c(1, 2); sc0 <- c(2,10)
# Stochastic EM algorithm
a <- weibullRMM_SEM(t, d, lambda = l0, shape = sh0, scale = sc0, maxit = 200)
summary(a) # Parameters estimates etc
plotweibullRMM(a) # default plot of St-EM sequences