Icens: EM – R documentation

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EM

A function to compute the NPMLE of p based on the incidence matrix A.

Description

The incidence matrix, A is the m by n matrix that represents the data. There are m probabilities that must be estimated. The EM, or expectation maximization, method is applied to these data.

Usage

EM(A, pvec, maxiter=500, tol=1e-12)

Arguments

`A`	The incidence matrix.
`pvec`	The probability vector.
`maxiter`	The maximum number of iterations.
`tol`	The tolerance used to judge convergence.

Details

Lots.

Value

An object of class icsurv containing the following components:

`pf`	The NPMLE of the probability vector.
`numiter`	The number of iterations used.
`converge`	A boolean indicating whether the algorithm converged.
`intmap`	If present indicates the real representation of the support for the values in `pf`.

Author(s)

Alain Vandal and Robert Gentleman.

References

The EM algorithm applied to the maximal cliques of the intersection graph of the censored data. The empirical distribution function with arbitrarily grouped, censored and truncated data, B. W. Turnbull, 1976, JRSS;B.

Examples

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

Icens

NPMLE for Censored and Truncated Data

v1.62.0

Artistic-2.0

Authors

R. Gentleman and Alain Vandal

Initial release

EM