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Lind, J.C.; Wiens, D.P.; Yohai, V.J. "Robust minimum information loss estimation" (2013) Computational Statistics and Data Analysis. 65:98-112
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Abstract:

Two robust estimators of a matrix-valued location parameter are introduced and discussed. Each is the average of the members of a subsample - typically of covariance or crosss-pectrum matrices - with the subsample chosen to minimize a function of its average. In one case this function is the Kullback-Leibler discrimination information loss incurred when the subsample is summarized by its average; in the other it is the determinant, subject to a certain side condition. For each, the authors give an efficient computing algorithm, and show that the estimator has, asymptotically, the maximum possible breakdown point. The main motivation is the need for efficient and robust estimation of cross-spectrum matrices, and they present a case study in which the data points originate as multichannel electroencephalogram recordings but are then summarized by the corresponding sample cross-spectrum matrices. © 2012 Elsevier B.V. All rights reserved.

Registro:

Documento: Artículo
Título:Robust minimum information loss estimation
Autor:Lind, J.C.; Wiens, D.P.; Yohai, V.J.
Filiación:Centre for Psychiatric Assessment and Therapeutics, Alberta Hospital Edmonton, Edmonton, AB T5J 2J7, Canada
Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB T6G 2G1, Canada
Departmento de Matemática, Facultad de Ciencias Exactas Y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
Palabras clave:Breakdown; Covariance; Cross-spectrum matrix; Electroencephalogram recording; Genetic algorithm; Minimum covariance determinant; Minimum information loss determinant estimate; Spectrum; Trimmed minimum information loss estimate; Covariance matrix; Electroencephalography; Genetic algorithms; Spectroscopy; Breakdown; Covariance; Cross spectra; Minimum covariance determinant; Minimum information loss; Spectrum; Matrix algebra
Año:2013
Volumen:65
Página de inicio:98
Página de fin:112
DOI: http://dx.doi.org/10.1016/j.csda.2012.06.011
Título revista:Computational Statistics and Data Analysis
Título revista abreviado:Comput. Stat. Data Anal.
ISSN:01679473
CODEN:CSDAD
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01679473_v65_n_p98_Lind

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Citas:

---------- APA ----------
Lind, J.C., Wiens, D.P. & Yohai, V.J. (2013) . Robust minimum information loss estimation. Computational Statistics and Data Analysis, 65, 98-112.
http://dx.doi.org/10.1016/j.csda.2012.06.011
---------- CHICAGO ----------
Lind, J.C., Wiens, D.P., Yohai, V.J. "Robust minimum information loss estimation" . Computational Statistics and Data Analysis 65 (2013) : 98-112.
http://dx.doi.org/10.1016/j.csda.2012.06.011
---------- MLA ----------
Lind, J.C., Wiens, D.P., Yohai, V.J. "Robust minimum information loss estimation" . Computational Statistics and Data Analysis, vol. 65, 2013, pp. 98-112.
http://dx.doi.org/10.1016/j.csda.2012.06.011
---------- VANCOUVER ----------
Lind, J.C., Wiens, D.P., Yohai, V.J. Robust minimum information loss estimation. Comput. Stat. Data Anal. 2013;65:98-112.
http://dx.doi.org/10.1016/j.csda.2012.06.011