BJnoint {emplik}R Documentation

The Buckley-James censored regression estimator without intercept term

Description

Compute the Buckley-James estimator in the regression model

y_i = beta x_i + epsilon_i

with right censored y.

Usage

BJnoint(x, y, delta, beta0 = NA, maxiter=30, error = 0.00001)

Arguments

x a matrix or vector containing the covariate, one row per observation.
y a numeric vector of length N, censored responses.
delta a vector of length N, delta=0/1 for censored/uncensored.
beta0 an optional vector for starting value of iteration.
maxiter an optional integer to control iterations.
error an optional positive value to control interations.

Details

If your model do have an intercept term, then you should use the function bj( ) in the Design library.

This function is included here mainly to produce the estimator value that may provide some useful info with function bjtest( ). For example you may want to test the beta value close to the Buckley-James estimator.

Value

A list with the following components:

beta the Buckley-James estimator.
iteration number of iterations performed.

Author(s)

Mai Zhou.

References

Buckley, J. and James, I. (1979). Biometrika

Owen, A. (1990). Empirical likelihood ratio confidence regions. Ann. Statist. 18 90-120.

Examples

x <- matrix(c(rnorm(50,mean=1), rnorm(50,mean=2)), ncol=2,nrow=50)
## Suppose now we wish to test Ho: 2mu(1)-mu(2)=0, then
y <- 2*x[,1]-x[,2]
xx <- c(28,-44,29,30,26,27,22,23,33,16,24,29,24,40,21,31,34,-2,25,19)

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