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MLEcens (version 0.1-2)

Computation of the MLE for bivariate (interval) censored data

Description

This package contains functions to compute the nonparametric maximum likelihood estimator (MLE) for the bivariate distribution of (X,Y), when realizations of (X,Y) cannot be observed directly. To be more precise, we consider the situation where we observe a set of rectangles (that we call 'observation rectangles') that are known to contain the unobservable realizations of (X,Y). We compute the MLE based on such a set of rectangles. The methods can also be used for univariate censored data (see data set 'cosmesis'), and for censored data with competing risks (see data set 'menopause'). We also provide functions to visualize the observed data and the MLE. (This package contains the functionality of the R-package 'bicreduc', which will no longer be maintained.)

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Version

Install

install.packages('MLEcens')

Monthly Downloads

2,607

Version

0.1-2

License

GPL (version 2 or later)

Maintainer

Marloes Maathuis

Last Published

September 21st, 2024

Functions in MLEcens (0.1-2)

plotCDF1

Create a marginal CDF (or survival function) plot of the MLE
plotDens1

Create a univariate density plot of the MLE
ex

Example data set (artificial)
plotCDF2

Create a bivariate CDF (or survival function) plot of the MLE
menopause

Menopause data
plotCM

Plot a clique matrix
menopauseMod

Modified menopause data
computeMLE

Compute the MLE for bivariate censored data
real2canon

Transform a set of rectangles into canonical rectangles
plotHM

Plot a height map
plotRects

Plot a set of rectangles
canon2real

Transform (intersections of) canonical rectangles back to their original coordinates
actg181Mod

Modified data from the Aids Clinical Trials Group protocol ACTG 181
actg181

Data from the Aids Clinical Trials Group protocol ACTG 181
reduc

Determine areas of possible mass support of the MLE
cosmesis

Breast cosmesis data
plotDens2

Create a bivariate density plot of the MLE