Icens (version 1.44.0)

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.

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.

Details

Lots.

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.

See Also

VEM, ISDM, EMICM, PGM

Examples

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

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