Fuller Measurement Error Models

99. Auflage 2009
ISBN: 978-0-470-31733-4
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 480 Seiten, E-Book

Reihe: Wiley Series in Probability and Statistics

The Wiley-Interscience Paperback Series consists of selected booksthat have been made more accessible to consumers in an effort toincrease global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists.
"The effort of Professor Fuller is commendable . . . [the book]provides a complete treatment of an important and frequentlyignored topic. Those who work with measurement error models willfind it valuable. It is the fundamental book on the subject, andstatisticians will benefit from adding this book to theircollection or to university or departmental libraries."
-Biometrics
"Given the large and diverse literature on measurementerror/errors-in-variables problems, Fuller's book is most welcome.Anyone with an interest in the subject should certainly have thisbook."
-Journal of the American Statistical Association
"The author is to be commended for providing a completepresentation of a very important topic. Statisticians working withmeasurement error problems will benefit from adding this book totheir collection."
-Technometrics
" . . . this book is a remarkable achievement and the product ofimpressive top-grade scholarly work."
-Journal of Applied Econometrics
Measurement Error Models offers coverage of estimation forsituations where the model variables are observed subject tomeasurement error. Regression models are included with errors inthe variables, latent variable models, and factor models. Resultsfrom several areas of application are discussed, including recentresults for nonlinear models and for models with unequal variances.The estimation of true values for the fixed model, prediction oftrue values under the random model, model checks, and the analysisof residuals are addressed, and in addition, procedures areillustrated with data drawn from nearly twenty real data sets.

Autoren/Hrsg.

Fuller, Wayne A.

Inhaltsverzeichnis

List of Examples.
List of Principal Results.
List of Figures.
1. A Single Explanatory Variable.
2. Vector Explanatory Variables.
3. Extensions of the Single Relation Model.
4. Multivariate Models.
Bibliography.
Author Index.
Subject Index.

Über Autor(innen)

WAYNE A. FULLER, PhD, is Distinguished Professor Emeritus inthe Department of Economics at Iowa State University. He is aFellow of the American Statistical Association, EconometricSociety, and Institute of Mathematical Statistics, and he is also amember of the International Statistical Institute.