plotly_spRMM {mixtools} | R Documentation |
Plot output from Stochastic EM algorithm for semiparametric scaled mixture of censored data using plotly
.
Description
This is an updated version of plotspRMM
function. For technical details, please refer to plotspRMM.
Usage
plotly_spRMM(sem, tmax = NULL,
width = 3 , col = '#1f77b4', cex = 3,
title.size = 15 ,
title.x = 0.5 , title.y = 0.95,
xlab.size = 15 , xtick.size=15 ,
ylab.size = 15 , ytick.size=15)
Arguments
sem |
An object returned by |
tmax |
The max time for |
width |
Width of lines. |
col |
Color of lines. |
cex |
Size of dots. |
title.size |
Size of the main title. |
title.x |
Horizontal position of the main title. |
title.y |
Vertical position of the main title. |
xlab.size |
Size of the label of X-axis. |
xtick.size |
Size of the tick of X-axis. |
ylab.size |
Size of the label of Y-axis. |
ytick.size |
Size of the tick of Y-axis. |
Value
The four plots 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: spRMM_SEM
, plotspRMM
.
Other models and algorithms for censored lifetime data
(name convention is model_algorithm):
expRMM_EM
,
weibullRMM_SEM
.
Examples
## Not run:
n=500 # sample size
m=2 # nb components
lambda=c(0.4, 0.6) # parameters
meanlog=3; sdlog=0.5; scale=0.1
set.seed(12)
# simulate a scaled mixture of lognormals
x <- rlnormscalemix(n, lambda, meanlog, sdlog, scale)
cs=runif(n,20,max(x)+400) # Censoring (uniform) and incomplete data
t <- apply(cbind(x,cs),1,min)
d <- 1*(x <= cs)
tauxc <- 100*round( 1-mean(d),3)
cat(tauxc, "percents of data censored.\n")
c0 <- c(25, 180) # data-driven initial centers (visible modes)
sc0 <- 25/180 # and scaling
s <- spRMM_SEM(t, d, scaling = sc0, centers = c0, bw = 15, maxit = 100)
plotly_spRMM(s) # default
summary(s) # S3 method for class "spRMM"
## End(Not run)