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Please use this identifier to cite or link to this item: http://hdl.handle.net/2328/26394

Title: Analytic perturbations and systematic bias in staistical modeling and inference
Authors: Filar, Jerzy A
Hudson, Irene
Mathew, Thomas
Sinha, Bimal
Keywords: Mathematics
Analytic perturbation
Design matrix
Factor analysis
Issue Date: 2008
Publisher: Institute of Mathematical Statistics
Citation: Filar, J.A., Hudson, I., Mathew, T. and Sinha, B., 2008. Analytic perturbations and systematic bias in statistical modeling and inference. IMS Collection 2008, 1, 17-34.
Abstract: In 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.
Description: Source: N. Balakrishnan, Edsel A. Peña and Mervyn J. Silvapulle, eds., Beyond Parametrics in Interdisciplinary Research: Festschrift in Honor of Professor Pranab K. Sen (Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2008), 17-34.
URI: http://hdl.handle.net/2328/26394
ISSN: 1939-4039
Appears in Collections:Computer Science, Engineering and Mathematics - Collected Works

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