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Measurement Error Models by Wayne A. Fuller
USD13,99
Aproximadamente12,05 EUR
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Estado:
En muy buen estado
Libro que se ha leído y que no tiene un aspecto nuevo, pero que está en un estado excelente. No hay desperfectos visibles en la tapa y se incluye sobrecubierta, si procede, para las tapas duras. Todas las páginas están en perfecto estado, sin arrugas ni roturas y no falta ninguna. El texto no está subrayado ni resaltado de forma alguna, y no hay anotaciones en los márgenes. Puede presentar marcas de identificación mínimas en la contraportada o las guardas. Muy poco usado. Consulta el anuncio del vendedor para obtener más información y la descripción de cualquier posible imperfección.
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Recogida local gratis en Mebane, North Carolina, Estados Unidos.
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USD5,38 (aprox. 4,63 EUR) USPS Media MailTM.
Ubicado en: Mebane, North Carolina, Estados Unidos
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Entrega prevista entre el sáb. 28 jun. y el sáb. 5 jul.
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N.º de artículo de eBay:316773828513
Última actualización el 26 jun 2025 03:13:25 H.EspVer todas las actualizacionesVer todas las actualizaciones
Características del artículo
- Estado
- Educational Level
- Adult & Further Education
- Level
- Scholarly & Professional
- Country/Region of Manufacture
- United States
- ISBN
- 9780471861874
Acerca de este producto
Product Identifiers
Publisher
Wiley & Sons, Incorporated, John
ISBN-10
0471861871
ISBN-13
9780471861874
eBay Product ID (ePID)
433925
Product Key Features
Number of Pages
464 Pages
Publication Name
Measurement Error Models
Language
English
Subject
Probability & Statistics / General
Publication Year
1987
Features
Revised
Type
Textbook
Subject Area
Mathematics
Series
Wiley Series in Probability and Statistics Ser.
Format
Hardcover
Dimensions
Item Height
1.1 in
Item Weight
23.8 Oz
Item Length
9.3 in
Item Width
6.2 in
Additional Product Features
Edition Number
99
Intended Audience
Scholarly & Professional
LCCN
86-028186
Dewey Edition
22
Series Volume Number
204
Illustrated
Yes
Dewey Decimal
511.43
Table Of Content
A Single Explanatory Variable. Vector Explanatory Variables. Extensions of the Single Relation Model. Multivariate Models. Appendixes. Bibliography. Index.
Edition Description
Revised edition
Synopsis
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., 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., 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.
LC Classification Number
QA275.F85 1987
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