MLEcens (version 0.1-2)

plotDens1: Create a univariate density plot of the MLE

Description

This function creates a univariate density plot of the MLE. To be precise, it can plot the density (d/dx) P(X

Usage

plotDens1(mle, margin, int=NULL, col=1, lty=1, add=FALSE,
          xlim=NULL, ylim=NULL, xlab="", ylab="", main="", sub="")

Arguments

mle

List with elements 'p' and 'rects', as outputted by computeMLE.

margin

Indicates which margin should be plotted: 1 = x-margin, 2 = y-margin. So if margin=1, the MLE for (d/dx) P(X

int

This indicates the range of interest of the variable that was not chosen in margin. If int is specified, it should be of the form c(a,b), with a

col

Line color. The default value is 1="black".

lty

Line type. The default value is 1="solid".

add

Logical, indicating if the lines should be added to an existing plot. The default value is FALSE.

xlim

Range for the horizontal axis, defaulting to the range of x-coordinates (if margin=1) or y-coordinates (if margin=2) of the relevant corners of maximal interesctions.

ylim

Range for the vertical axis, defaulting to the range of values of the estimate.

xlab,ylab

Labels of the x- and y-axis. The default values are empty.

main

Title of the plot.

sub

Sub title of the plot.

Value

• No value is returned.

concept

• nonparametric maximum likelihood estimator
• censored data

Details

In many cases we assign specific values to represent +/- infinity and (see, e.g., actg181). Note that these values determine the size of maximal intersections that extend to +/- infinity, and hence they also determine the value of the density at such maximal intersections. The value of the density at such maximal intersections is therefore meaningless.

See Also

computeMLE

Examples

# Load example data:
data(ex)

# Compute the MLE:
mle <- computeMLE(ex)

# Bivariate density plot of the MLE:
#   Numbers represent the mass p in the maximal intersections
par(mfrow=c(2,2))
plotDens2(mle, xlim=range(ex[,1:2]), ylim=range(ex[,3:4]), 
 col="lightgray", main="Bivariate density plot of the MLE", 
 key=FALSE, numbers=TRUE)
plotRects(ex, add=TRUE)

# Univariate density plots of the MLE:

#   Plot of the marginal density of Y
plotDens1(mle, margin=2, xlim=range(ex[,3:4]), 
 main="Marginal density plot, 
 y-margin", xlab="y", ylab=expression(f[Y](y))) 

#   Plot of the marginal density of X 
plotDens1(mle, margin=1, xlim=range(ex[,1:2]), 
 main="Marginal density plot, 
 x-margin", xlab="x", ylab=expression(f[X](x)))