Current status linear regression

Title

Current status linear regression

 Author

Groeneboom, P. (TU Delft Statistics) ORCID 0000-0001-8027-8114
Hendrickx, K. (TU Delft Statistics; University of Hasselt)

Date

2018

 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.


 Subject

Current status
Linear regression
MLE
Semiparametric model

 To reference this document use:

http://resolver.tudelft.nl/uuid:6636cebd-0327-4083-87dc-8f2fe9442e4e

 DOI

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

 ISSN

0090-5364

 Source

Annals of Statistics, 46 (4), 1415-1444

 Part of collection

Institutional Repository

 Document type

journal article

 Rights

© 2018 P. Groeneboom, K. Hendrickx
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