plotseq.npEM: Plotting sequences of estimates from non- or semiparametric...

In mixtools: Tools for Analyzing Finite Mixture Models

Plotting sequences of estimates from non- or semiparametric EM-like Algorithm

Description

Returns plots of the sequences of scalar parameter estimates along iterations from an object of class npEM.

Usage

  ## S3 method for class 'npEM'
plotseq(x, ...)

Arguments

x	an object of class npEM, as output by npEM or spEMsymloc
...	further parameters that are passed to plot

Details

plotseq.npEM returns a figure with one plot for each component proportion, and, in the case of spEMsymloc, one plot for each component mean.

References

• Benaglia, T., Chauveau, D., and Hunter, D. R. (2009), An EM-like algorithm for semi- and non-parametric estimation in multivariate mixtures, Journal of Computational and Graphical Statistics (to appear).

• Bordes, L., Chauveau, D., and Vandekerkhove, P. (2007), An EM algorithm for a semiparametric mixture model, Computational Statistics and Data Analysis, 51: 5429-5443.

See Also

plot.npEM, rnormmix, npEM, spEMsymloc

Examples

## Example from a normal location mixture
n <- 200
set.seed(100)
lambda <- c(1/3,2/3)
mu <- c(0, 4); sigma<-rep(1, 2)
x <- rnormmix(n, lambda, mu, sigma)
b <- spEMsymloc(x, mu0=c(-1, 2), stochastic=FALSE)
plotseq(b)
bst <- spEMsymloc(x, mu0=c(-1, 2), stochastic=TRUE)
plotseq(bst)

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