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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/25157

Title: Current status linear regression
Authors: Hendrickx, Kim
Groeneboom, Piet
Issue Date: 2017
Citation: ANNALS OF STATISTICS,, p. 1-31
Status: In Press
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 non-monotone 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.
URI: http://hdl.handle.net/1942/25157
ISSN: 0090-5364
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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