Notice bibliographique
- Notice
Type(s) de contenu et mode(s) de consultation : Texte noté : électronique
Auteur(s) : Kosorok, Michael R.
Titre(s) : Introduction to empirical processes and semiparametric inference [Texte électronique] / Michael R. Kosorok
Publication : New York, N.Y., USA : Springer, cop. 2008
Description matérielle : 1 ressource dématérialisée
Collection : Springer series in statistics
Note(s) : Includes bibliographical references (pages 459-469) and indexes
"This book provides a self-contained, linear, and unified introduction to empirical
processes and semiparametric inference. These powerful research techniques are surprisingly
useful for developing methods of statistical reference for complex models and in understanding
the properties of such methods. The targeted audience includes statisticians, biostatisticians,
and other researchers with a background in mathematical statistics who have an interest
in learning about and doing research in empirical processes and semiparametric inference
but who would like to have a friendly and gradual introduction to the area. The book
can be used either as a research reference or as a textbook. The level of the book
is suitable for a second year graduate course in statistics or biostatistics, provided
the students have had a year of graduate level mathematical statistics and a semester
of provability."--Jacket
Autre(s) forme(s) du titre :
- Autre forme du titre : Empirical processes and semiparametric inference
- Autre forme du titre : Semiparametric inference
Sujet(s) : Empirisme -- Modèles mathématiques
Estimation de paramètres -- Modèles mathématiques
Estimation, Théorie de l' -- Modèles mathématiques
Systèmes stochastiques -- Modèles mathématiques
Genre ou forme : Études de cas
Indice(s) Dewey :
146.44 (23e éd.) = Empirisme ; 519.23 (23e éd.) = Processus aléatoires
Identifiants, prix et caractéristiques : ISBN 9780387749785
Identifiant de la notice : ark:/12148/cb44643703k
Notice n° :
FRBNF44643703
(notice reprise d'un réservoir extérieur)
Table des matières : Introduction ; An overview of empirical processes ; Overview of semiparametric inference
; Case studies I ; Introduction to empirical processes ; Preliminaries for empirical
processes ; Stochastic convergence ; Empirical process methods ; Entropy calculations
; Bootstrapping empirical processes ; Additional empirical process results ; The
functional delta method ; Z-estimators ; M-estimators --- Case studies II ; Introduction
to semiparametric inference ; Semiparametric models and efficiency ; Efficient inference
for finite-dimensional parameters ; Efficient inference for infinite-dimensional
parameters ; Semiparametric M-estimation ; Case studies III.
