EMICM {Icens}R Documentation

Compute the NPMLE for censored data using the EMICM.

Description

An implementation of the hybrid EM ICM (Iterative convex minorant) estimator of the distribution function proposed by Wellner and Zahn (1997).

Usage

EMICM(A, EMstep=TRUE, ICMstep=TRUE, keepiter=FALSE, tol=1e-07,
maxiter=1000) 

Arguments

A Either the m by n clique matrix or the n by 2 matrix containing the event time intervals.
EMstep Boolean, indicating whether to take an EM step in the iteration.
ICMstep Boolean, indicating whether to take an ICM step.
keepiter Boolean determining whether to keep the iteration states.
tol The maximal L1 distance between successive estimates before stopping iteration.
maxiter The maximal number of iterations to perform before stopping.

Details

Lots, and they're complicated too!

Value

An object of class icsurv containing the following components:

pf The estimated probabilities.
sigma The NPMLE of the survival function on the maximal antichains.
weights The diagonal of the likelihood function's second derivative.
lastchange A vector of differences between the last two iterations.
numiter The total number of iterations performed.
iter Is only present if keepiter is true; states of sigma during the iteration.
intmap The real representation associated with the probabilities reported in pf.

Author(s)

Alain Vandal and Robert Gentleman

References

A hybrid algorithm for computation of the nonparametric maximum likelihood estimator from censored data, J. A. Wellner and Y. Zhan, 1997, JASA.

See Also

EM,VEM, PGM

Examples

  data(cosmesis)
  csub1 <- subset(cosmesis, subset=Trt==0, select=c(L,R))
  EMICM(csub1)
  data(pruitt)
  EMICM(pruitt)

[Package Icens version 0.5 Index]