PDF Ebook Measurement Error Models, by Wayne A. Fuller
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Measurement Error Models, by Wayne A. Fuller
PDF Ebook Measurement Error Models, by Wayne A. Fuller
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The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
"The effort of Professor Fuller is commendable . . . [the book] provides a complete treatment of an important and frequently ignored topic. Those who work with measurement error models will find it valuable. It is the fundamental book on the subject, and statisticians will benefit from adding this book to their collection or to university or departmental libraries."
-Biometrics
"Given the large and diverse literature on measurement error/errors-in-variables problems, Fuller's book is most welcome. Anyone with an interest in the subject should certainly have this book."
-Journal of the American Statistical Association
"The author is to be commended for providing a complete presentation of a very important topic. Statisticians working with measurement error problems will benefit from adding this book to their collection."
-Technometrics
" . . . this book is a remarkable achievement and the product of impressive top-grade scholarly work."
-Journal of Applied Econometrics
Measurement Error Models offers coverage of estimation for situations where the model variables are observed subject to measurement error. Regression models are included with errors in the variables, latent variable models, and factor models. Results from several areas of application are discussed, including recent results for nonlinear models and for models with unequal variances. The estimation of true values for the fixed model, prediction of true values under the random model, model checks, and the analysis of residuals are addressed, and in addition, procedures are illustrated with data drawn from nearly twenty real data sets.
- Sales Rank: #2325971 in Books
- Published on: 1987-06-30
- Original language: English
- Number of items: 1
- Dimensions: 9.37" h x 1.14" w x 6.30" l, 1.76 pounds
- Binding: Hardcover
- 440 pages
Review
"…very interesting for the theory it contains… enjoyable and useful." (Zentralblatt MATH, 1107, 64)
From the Publisher
This valuable book-length treatment of the field offers coverage of estimation for situations where the model variables are observed subject to measurement error. Included are regression models with errors in the variables, latent variable models, and factor models. Brings together results from several areas of application, including discussion of recent results for nonlinear models and for models with unequal variances. Also explained are the estimation of true values for the fixed model, prediction of true values under the random model, model checks, and the analysis of residuals. Procedures are illustrated with data drawn from nearly twenty real-data sets.
From the Back Cover
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
"The effort of Professor Fuller is commendable . . . [the book] provides a complete treatment of an important and frequently ignored topic. Those who work with measurement error models will find it valuable. It is the fundamental book on the subject, and statisticians will benefit from adding this book to their collection or to university or departmental libraries."
—Biometrics
"Given the large and diverse literature on measurement error/errors-in-variables problems, Fuller's book is most welcome. Anyone with an interest in the subject should certainly have this book."
—Journal of the American Statistical Association
"The author is to be commended for providing a complete presentation of a very important topic. Statisticians working with measurement error problems will benefit from adding this book to their collection."
—Technometrics
" . . . this book is a remarkable achievement and the product of impressive top-grade scholarly work."
—Journal of Applied Econometrics
Measurement Error Models offers coverage of estimation for situations where the model variables are observed subject to measurement error. Regression models are included with errors in the variables, latent variable models, and factor models. Results from several areas of application are discussed, including recent results for nonlinear models and for models with unequal variances. The estimation of true values for the fixed model, prediction of true values under the random model, model checks, and the analysis of residuals are addressed, and in addition, procedures are illustrated with data drawn from nearly twenty real data sets.
Most helpful customer reviews
0 of 5 people found the following review helpful.
A short note
By Jacek Czaplicki
Fuller's monograph on measurement error models is a unique work; highly professional with no so many competitors in this league. It is a unite paper. However, its position is peculiar. It is not so popular amongst econometricians, though they are prepared to read and understand the text easily. Usually, econometricians have no inclination to analyse their problems looking through imperfections contained in data and models. The book should be of special usefulness for engineers, but they are - in turn - not prepared to take such heavy technometrics load. As a rule they/we are not ready to follow considerations. It's a pity because the book is outstanding.
The author presents knowledge from the highest shelf. However, being on such high level he used to present parts of the text nonchalantly with lack of appropriate accuracy changing sometimes commonly used notations or so. For people familiar with statistics it does not matter but for engineers it might be a significant barrier to understand the text. It looks that the most important point for the author is consideration; a text reader is far at the background. Author of a book should be always at the first position.
5 of 16 people found the following review helpful.
Paperback at $100?
By Kenny
This review has nothing to do with the content of the book. It is the reprint of the 1987 classic on measurement error model, only NOW as PAPERBACK, and Wiley has guts to price it over $100.
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