<p>Example data set with artificial bivariate interval censored data. These
  data are used to illustrate various functions of this R-package.</p>

datasets

We provide 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 in R^2 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.

Marloes Maathuis

MLEcens

Computation of the MLE for Bivariate Interval Censored Data

ex function

<p>A matrix containing 6 rows and 4 columns. Each row    
(x1,x2,y1,y2) represents a rectangle that is known to contain 
the unobservable realization of the variables of interest (X,Y).
The point (x1,y1) is the lower left corner of the rectangle and
(x2,y2) is the upper right corner of the rectangle.</p>

ex: Example data set (artificial)

Description

Usage

Arguments

Format

Examples