Presentación | Participantes | Bibliografía (DML-E) | Bibliografía adicional | Enlaces de interés | Otros proyectos DML | Ayuda  
INICIO | 15 de abril de 2024
  

Robust estimation and forecasting for beta-mixed hierarchical models of grouped binary data.

Título inglés Robust estimation and forecasting for beta-mixed hierarchical models of grouped binary data.
Título español Estimación robusta y pronóstico para modelos jerárquicos beta-mezclados de datos binarios agrupados.
Autor/es Pashkevich, Maxim A. ; Kharin, Yurij S.
Organización Dep. Math. Model. & Data Anal. Fac. Appl. Math. Comput. Sci. Belarusian State Univ., Minsk, Bielorrusia
Revista 1696-2281
Publicación 2004, 28 (2): 125-160, 33 Ref.
Tipo de documento articulo
Idioma Inglés
Resumen inglés The paper focuses on robust estimation and forecasting techniques for grouped binary data with misclassified responses. It is assumed that the data are described by the beta-mixed hierarchical model (the beta-binomial or the beta-logistic), while the misclassifications are caused by the stochastic additive distorsions of binary observations. For these models, the effect of ignoring the misclassifications is evaluated and expressions for the biases of the method-of-moments estimators and maximum likelihood estimators, as well as expressions for the increase in the mean square error of forecasting for the Bayes predictor are given. To compensate the misclassification effects, new consistent estimators and a new Bayes predictor, which take into account the distortion model, are constructed. The robustness of the developed techniques is demostrated via computer simulations and a real-life case study.
Clasificación UNESCO 120913
Palabras clave español Inferencia paramétrica ; Estimadores robustos ; Modelo jerárquico
Código MathReviews MR2116188
Icono pdf Acceso al artículo completo
Equipo DML-E
Instituto de Ciencias Matemáticas (ICMAT - CSIC)
rmm()icmat.es