Maximum Penalized Likelihood Estimation

Name: Maximum Penalized Likelihood Estimation
Brand: Springer-Verlag New York Inc.
SKU: 9781441929280
Price: 1104.81 RON
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Volume I: Density Estimation

Autor: P.P.B. Eggermont, V.N. LaRiccia

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Editura: Springer-Verlag New York Inc.

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This book deals with parametric and nonparametric density estimation from the maximum (penalized) li...

Informații despre carte

Autor

P.P.B. Eggermont, V.N. LaRiccia

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2010

Pagini

512

EAN

9781441929280

ISBN

1441929282

Enbook ID

01421665

Editura

Springer-Verlag New York Inc.

Greutate

807

Dimensiuni

155 x 235 x 29

Descriere completă

This book deals with parametric and nonparametric density estimation from the maximum (penalized) likelihood point of view, including estimation under constraints. The focal points are existence and uniqueness of the estimators, almost sure convergence rates for the L1 error, and data-driven smoothing parameter selection methods, including their practical performance. The reader will gain insight into technical tools from probability theory and applied mathematics.This text deals with parametric and nonparametric density estimation from the maximum (penalized) likelihood point of view, including estimation under constraints such as unimodality and log-concavity. It is intended for graduate students in statistics, applied mathematics, and operations research, as well as for researchers and practitioners in the field.§The focal points are existence and uniqueness of the estimators, almost sure convergence rates for the L1 error, and data-driven smoothing parameter selection methods, including their practical performance. The reader will gain insight into some of the generally applicable technical tools from probability theory (discrete parameter martingales) and applied mathematics (boundary, value problems and integration by parts tricks.) Convexity and convex optimization, as applied to maximum penalized likelihood estimation, receive special attention.§The authors are with the Statistics Program of the Department of Food and Resource Economics in the College of Agriculture at the University of Delaware.

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Maximum Penalized Likelihood Estimation

Volume I: Density Estimation

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Descriere completă

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