Analytic perturbations and systematic bias in statistical modeling and inference

Simple item page
dc.creatorFilar, Jerzy A.
dc.creatorHudson, Irene
dc.creatorMathew, Thomas
dc.creatorSinha, Bimal
dc.date2008-05-15
dc.date.accessioned2026-07-07T12:18:53Z
dc.date.available2026-07-07T12:18:53Z
dc.descriptionIn this paper we provide a comprehensive study of statistical inference in linear and allied models which exhibit some analytic perturbations in their design and covariance matrices. We also indicate a few potential applications. In the theory of perturbations of linear operators it has been known for a long time that the so-called ``singular perturbations'' can have a big impact on solutions of equations involving these operators even when their size is small. It appears that so far the question of whether such undesirable phenomena can also occur in statistical models and their solutions has not been formally studied. The models considered in this article arise in the context of nonlinear models where a single parameter accounts for the nonlinearity.
dc.descriptionPublished in at http://dx.doi.org/10.1214/193940307000000022 the IMS Collections (http://www.imstat.org/publications/imscollections.htm) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0805.2228
dc.identifierhttp://arxiv.org/abs/0805.2228
dc.identifierIMS Collections 2008, Vol. 1, 17-34
dc.identifierdoi:10.1214/193940307000000022
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/212568
dc.subjectStatistics Theory
dc.subject15A99 (Primary) 62J99 (Secondary)
dc.titleAnalytic perturbations and systematic bias in statistical modeling and inference
dc.typetext

Files

Collections

arXiv