density.spEM: Normal kernel density estimate for semiparametric EM output

In mixtools: Tools for Analyzing Finite Mixture Models

Normal kernel density estimate for semiparametric EM output

Description

Takes an object of class spEM and returns an object of class density giving the kernel density estimate.

Usage

## S3 method for class 'spEM'
density(x, u=NULL, component=1, block=1, scale=FALSE, ...)

Arguments

x	An object of class npEM such as the output of the npEM or spEMsymloc functions.
u	Vector of points at which the density is to be evaluated
component	Mixture component number; should be an integer from 1 to the number of columns of x$posteriors.
block	Block of repeated measures. Only applicable in repeated measures case, for which x$blockid exists; should be an integer from 1 to max(x$blockid).
scale	Logical: If TRUE, multiply the density values by the corresponding mixing proportions found in x$lambdahat
...	Additional arguments; not used by this method.

Details

The bandwidth is taken to be the same as that used to produce the npEM object, which is given by x$bandwidth.

Value

density.spEM returns a list of type "density". See density for details. In particular, the output of density.spEM may be used directly by functions such as plot or lines.

See Also

spEM, spEMsymloc, plot.spEM

Examples

 
set.seed(100)
mu <- matrix(c(0, 15), 2, 3)
sigma <- matrix(c(1, 5), 2, 3)
x <- rmvnormmix(300, lambda = c(.4,.6), mu = mu, sigma = sigma)

d <- spEM(x, mu0 = 2, blockid = rep(1,3), constbw = TRUE) 
plot(d, xlim=c(-10, 40), ylim = c(0, .16), xlab = "", breaks = 30, 
     cex.lab=1.5, cex.axis=1.5) # plot.spEM calls density.spEM here

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