Plot sequences from the Stochastic EM algorithm for mixture of Weibull
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).
plotweibullRMM(a, title = NULL, rowstyle = TRUE, subtitle = NULL, ...)
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 |
The plot returned
Didier Chauveau
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. http://link.springer.com/article/10.1007/s00180-016-0661-7
Related functions:
weibullRMM_SEM, summary.mixEM.
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
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