Könyv Maximum Penalized Likelihood Estimation P.P.B. Eggermont

Maximum Penalized Likelihood Estimation

Volume I: Density Estimation

Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: Beszállítói készleten
Küldés 5-8 napon belül
76 883 Ft
This book deals with parametric and nonparametric density estimation from the maximum (penalized) li...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2010
oldal
512
EAN
9781441929280
ISBN
1441929282
Enbook ID
01421665
Súly
807
Méretek
155 x 235 x 29

Teljes leírás

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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