Current status linear regression

Groeneboom, P.; Hendrickx, K.

doi:10.1214/17-AOS1589

Current status linear regression

Journal article (2018)

Authors

P. Groeneboom Statistics

K. Hendrickx University of Hasselt, Statistics

Research Group

Statistics

DOI: https://doi.org/10.1214/17-AOS1589

MLE Linear regression Current status Semiparametric model

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Published Date

2018

Language

English

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Research Group

Statistics

Abstract

We construct n-consistent and asymptotically normal estimates for the finite dimensional regression parameter in the current status linear regression model, which do not require any smoothing device and are based on maximum likelihood estimates (MLEs) of the infinite dimensional parameter. We also construct estimates, again only based on these MLEs, which are arbitrarily close to efficient estimates, if the generalized Fisher information is finite. This type of efficiency is also derived under minimal conditions for estimates based on smooth nonmonotone plug-in estimates of the distribution function. Algorithms for computing the estimates and for selecting the bandwidth of the smooth estimates with a bootstrap method are provided. The connection with results in the econometric literature is also pointed out.

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