La estimación de proporciones mediante técnicas Bayesianas [Estimation of Ratios Using Bayesian Techniques]
Author(s) -
E. Inmaculada De La Fuente,
Luis María Lozano,
Concepción San Luis Costas,
Eduardo GarcíaCueto,
Joan Guàrdia Olmos,
María E Fernández Martín,
María Isabel Barbero,
Montserrat Freixa Niella,
Maribel Peró,
Ana Rosa Ortega,
Gustavo R. Cañadas,
Daniela Padierna Alcaraz,
Montecino Díaz,
Ignacio Predosa
Publication year - 2008
Publication title -
acción psicológica
Language(s) - English
Resource type - Journals
eISSN - 2255-1271
pISSN - 1578-908X
DOI - 10.5944/ap.5.2.455
Subject(s) - point estimation , bayes' theorem , bayesian probability , parametric statistics , estimation , inference , interval estimation , bayesian inference , bayes estimator , mathematics , statistics , computer science , econometrics , confidence interval , artificial intelligence , management , economics
Resumen Los procedimientos de estimacion basados en el teorema de Bayes son inusuales en los diferentes ambitos de aplicacion de la inferencia parametrica clasica. El objetivo de este trabajo es presentar un esquema para la estimacion bayesiana de parametros bajo los supuestos de un modelo binomial. El procedimiento Bayes se estudia en comparacion con la aproximacion parametrica cl??sica, ambas opciones, en su version puntual y mediante intervalos de estimacion. Se presenta tambien un estudio de simulacion con diferentes tamanos muestrales en el que se ponen de manifiesto las ventajas del procedimiento bayesiano. Abstract The estimation procedures based on Bayes' Theorem are still an unusual option in many of the environments of classic parametric inference. The aim of this paper is to show an effective scheme for the use of Bayesian estimation of unknown parameters. We have opted to focus on the estimation of parameters under the assumption of a binomial model, so that it can be followed by all those situations that meet the aforementioned probabilistic model. This approximation was studied in comparison with the classic parametric approximation, both in its point version and by means of interval estimation. On a study, by simulating samples of several sizes, we obtained empirical evidence regarding the advantage of the Bayesian procedure.
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