The distribution of a linear predictor after model selection: Unconditional finite-sample distributions and asymptotic approximations

Hannes Leeb ()

Papers from arXiv.org

Abstract: We analyze the (unconditional) distribution of a linear predictor that is constructed after a data-driven model selection step in a linear regression model. First, we derive the exact finite-sample cumulative distribution function (cdf) of the linear predictor, and a simple approximation to this (complicated) cdf. We then analyze the large-sample limit behavior of these cdfs, in the fixed-parameter case and under local alternatives.

Date: 2006-11
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Published in IMS Lecture Notes--Monograph Series 2006, Vol. 49, 291-311

Downloads: (external link)
http://arxiv.org/pdf/math/0611186 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:math/0611186

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().