Icens: EMICM – R documentation

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EMICM

Compute the NPMLE for censored data using the EMICM.

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

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

`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.

Lots, and they're complicated too!

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`.

Alain Vandal and Robert Gentleman

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

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

NPMLE for Censored and Truncated Data

v1.62.0

Artistic-2.0

Authors

R. Gentleman and Alain Vandal

Initial release