plotmixt: Plot for 1- to 3-dimensional normal and t-mixture density...

In ks: Kernel Smoothing

Plot for 1- to 3-dimensional normal and t-mixture density functions

Description

Plot for 1- to 3-dimensional normal and t-mixture density functions.

Usage

plotmixt(mus, sigmas, Sigmas, props, dfs, dist="normal", draw=TRUE,
   deriv.order=0, which.deriv.ind=1, binned=TRUE, ...)

Arguments

mus	(stacked) matrix of mean vectors
sigmas	vector of standard deviations (1-d)
Sigmas	(stacked) matrix of variance matrices (2-d, 3-d)
props	vector of mixing proportions
dfs	vector of degrees of freedom
dist	"normal" - normal mixture, "t" - t-mixture
draw	flag to draw plot. Default is TRUE.
deriv.order	derivative order
which.deriv.ind	index of which partial derivative to plot
binned	flag for binned estimation of contour levels. Default is TRUE.
...	other graphics parameters, see plot.kde

Value

If draw=TRUE, the 1-d, 2-d plot is sent to graphics window, 3-d plot to graphics/RGL window. If draw=FALSE, then a kdde-like object is returned.

Examples

## bivariate 
mus <- rbind(c(0,0), c(-1,1))
Sigma <- matrix(c(1, 0.7, 0.7, 1), nr=2, nc=2) 
Sigmas <- rbind(Sigma, Sigma)
props <- c(1/2, 1/2)
plotmixt(mus=mus, Sigmas=Sigmas, props=props, display="filled.contour", lwd=1)

## trivariate 
mus <- rbind(c(0,0,0), c(-1,0.5,1.5))
Sigma <- matrix(c(1, 0.7, 0.7, 0.7, 1, 0.7, 0.7, 0.7, 1), nr=3, nc=3) 
Sigmas <- rbind(Sigma, Sigma)
props <- c(1/2, 1/2)
plotmixt(mus=mus, Sigmas=Sigmas, props=props, dfs=c(11,8), dist="t")

ks documentation built on Aug. 11, 2023, 1:10 a.m.