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Maximum Penalized Likelihood Estimation
Volume I: Density Estimation
Taschenbuch von Vincent N. Lariccia (u. a.)
Sprache: Englisch

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Beschreibung
This book is intended for graduate students in statistics and industrial mathematics, as well as researchers and practitioners in the field. We cover both theory and practice of nonparametric estimation. The text is novel in its use of maximum penalized likelihood estimation, and the theory of convex minimization problems (fully developed in the text) to obtain convergence rates. We also use (and develop from an elementary view point) discrete parameter submartingales and exponential inequalities. A substantial effort has been made to discuss computational details, and to include simulation studies and analyses of some classical data sets using fully automatic (data driven) procedures. Some theoretical topics that appear in textbook form for the first time are definitive treatments of I.J. Good's roughness penalization, monotone and unimodal density estimation, asymptotic optimality of generalized cross validation for spline smoothing and analogous methods for ill-posed least squares problems, and convergence proofs of EM algorithms for random sampling problems.
This book is intended for graduate students in statistics and industrial mathematics, as well as researchers and practitioners in the field. We cover both theory and practice of nonparametric estimation. The text is novel in its use of maximum penalized likelihood estimation, and the theory of convex minimization problems (fully developed in the text) to obtain convergence rates. We also use (and develop from an elementary view point) discrete parameter submartingales and exponential inequalities. A substantial effort has been made to discuss computational details, and to include simulation studies and analyses of some classical data sets using fully automatic (data driven) procedures. Some theoretical topics that appear in textbook form for the first time are definitive treatments of I.J. Good's roughness penalization, monotone and unimodal density estimation, asymptotic optimality of generalized cross validation for spline smoothing and analogous methods for ill-posed least squares problems, and convergence proofs of EM algorithms for random sampling problems.
Zusammenfassung
This reference book is intended for graduate students and researchers in statistics, industrial and engineering mathematics, and operations research.
Inhaltsverzeichnis
Parametric Maximum Likelihood Estimation * Parametric Maximum Likelihood Estimation in Action * Kernel Density Estimation * Maximum Likelihood Density Estimation * Monotone and Unimodal Densities * Choosing the Smoothing Parameter * Nonparametric Density Estimation in Action * Convex Minimization in Finite Dimensional Spaces * Convex Minimization in Infinite Dimensional Spaces * Convexity in Action
Details
Erscheinungsjahr: 2010
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Importe, Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xviii
512 S.
30 s/w Illustr.
ISBN-13: 9781441929280
ISBN-10: 1441929282
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Lariccia, Vincent N.
Eggermont, P. P. B.
Auflage: Softcover reprint of hardcover 1st edition 2001
Hersteller: Springer US
Springer New York
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 234 x 156 x 29 mm
Von/Mit: Vincent N. Lariccia (u. a.)
Erscheinungsdatum: 03.12.2010
Gewicht: 0,799 kg
Artikel-ID: 107253005
Zusammenfassung
This reference book is intended for graduate students and researchers in statistics, industrial and engineering mathematics, and operations research.
Inhaltsverzeichnis
Parametric Maximum Likelihood Estimation * Parametric Maximum Likelihood Estimation in Action * Kernel Density Estimation * Maximum Likelihood Density Estimation * Monotone and Unimodal Densities * Choosing the Smoothing Parameter * Nonparametric Density Estimation in Action * Convex Minimization in Finite Dimensional Spaces * Convex Minimization in Infinite Dimensional Spaces * Convexity in Action
Details
Erscheinungsjahr: 2010
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Importe, Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xviii
512 S.
30 s/w Illustr.
ISBN-13: 9781441929280
ISBN-10: 1441929282
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Lariccia, Vincent N.
Eggermont, P. P. B.
Auflage: Softcover reprint of hardcover 1st edition 2001
Hersteller: Springer US
Springer New York
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 234 x 156 x 29 mm
Von/Mit: Vincent N. Lariccia (u. a.)
Erscheinungsdatum: 03.12.2010
Gewicht: 0,799 kg
Artikel-ID: 107253005
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