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Statistical analysis of measurement error models and applications : proceedings of the AMS-IMS-SIAM joint summer research conference held June 10-16, 1989, with support from the National Science Foundation and the U.S. Army Research Office /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: AMS-IMS-SIAM Joint Summer Research Conference in the Mathematical Sciences on Statistical Analysis of Measurement Error Models and Applications Humboldt State University
Otros Autores: Brown, Philip J., 1944- (Editor ), Fuller, Wayne A. (Editor )
Formato: Electrónico Congresos, conferencias eBook
Idioma:Inglés
Publicado: Providence, Rhode Island : American Mathematical Society, [1990]
Colección:Contemporary mathematics (American Mathematical Society) ; 112.
Temas:
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Contents
  • Preface
  • General Problems
  • Some History of Functional and Structural Relationships
  • Errors-in-Variables Regression Problems in Epidemiology
  • Models with Latent Variables: LISREL Versus PLS
  • Prediction of True Values for the Measurement Error Model
  • Analysis of Residuals from Measurement Error Models
  • Errors-in-Variables Estimation in the Presence of Serially Correlated Observations
  • Nonlinear Models
  • Improvements of the Naive Approach to Estimation in Nonlinear Errors-in-Variables Regression Models
  • Structural Logistic Regression Measurement Error ModelsMeasurement Error Model Estimation Using Iteratively Weighted Least Squares
  • Problematic Points in Nonlinear Calibration
  • Instrumental Variable Estimation of the Nonlinear Measurement Error Model
  • A Likelihood Ratio Test for Error Covariance Specification in Nonlinear Measurement Error Models
  • Plotting Techniques for Errors-in-Variables Problems
  • Computational Aspects
  • Perturbation Theory and Least Squares with Errors in the Variables
  • Orthogonal Distance Regression
  • Computing Error Bounds for Regression ProblemsRobust Procedures
  • Asymptotic Robustness of Normal Theory Methods for the Analysis of Latent Curves
  • Bounded Influence Errors-in-Variables Regression
  • Bounded Influence Estimation in the Errors-in-Variables Model