06245nam 2200541Ia 450 991083059210332120180117165002.01-282-30772-X97866123077200-470-31666-70-470-31733-7(CKB)1000000000687540(StDuBDS)AH3916609(SSID)ssj0000340249(PQKBManifestationID)11266901(PQKBTitleCode)TC0000340249(PQKBWorkID)10364954(PQKB)10356474(MiAaPQ)EBC469407(PPN)15935580X(EXLCZ)99100000000068754019861110d1987 uy 0engur|||||||||||txtccrMeasurement error models[electronic resource] /Wayne A. FullerNew York Wileyc19871 online resource (xxiii, 440 p. )illustrationsWiley series in probability and mathematical statistics. Probability and mathematical statistics,0271-6356Includes bibliography and indexes.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.Offers coverage of estimation for situations where the model variables are observed subject to measurement error. This book includes regression models with errors in the variables, latent variable models, and factor models. It discusses results from areas of application, including results for nonlinear models and for models with unequal variances.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. 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.Wiley series in probability and mathematical statistics.Probability and mathematical statistics.Error analysis (Mathematics)Regression analysisError analysis (Mathematics)Regression analysis.511.43Fuller Wayne A116991MiAaPQMiAaPQMiAaPQBOOK9910830592103321Measurement error models197022UNINA