Constrained Bayes and Empirical Bayes Estimator Applications in Insurance Pricing
نویسندگان
چکیده
منابع مشابه
An Improved Bayes Empirical Bayes Estimator
Consider an experiment yielding an observable random quantity X whose distribution Fθ depends on a parameter θ with θ being distributed according to some distribution G0. We study the Bayesian estimation problem of θ under squared error loss function based on X, as well as some additional data available from other similar experiments according to an empirical Bayes structure. In a recent paper,...
متن کاملEmpirical Bayes and the James–Stein Estimator
Charles Stein shocked the statistical world in 1955 with his proof that maximum likelihood estimation methods for Gaussian models, in common use for more than a century, were inadmissible beyond simple oneor twodimensional situations. These methods are still in use, for good reasons, but Stein-type estimators have pointed the way toward a radically different empirical Bayes approach to high-dim...
متن کاملThe Empirical Bayes Estimator and Mixed Distributions
The empirical Bayes estimator of the probability of a successful event is deduced from mixed distributions. Specially, binomial and Poisson mixed distributions are analyzed. Some mixing distributions, well known in Reliability, Queuing Theory and other areas of Engineering, are considered. As it will be shown, a family of estimators with interesting characteristics is obtained for different mix...
متن کاملEmpirical Bayes Estimation in Nonstationary Markov chains
Estimation procedures for nonstationary Markov chains appear to be relatively sparse. This work introduces empirical Bayes estimators for the transition probability matrix of a finite nonstationary Markov chain. The data are assumed to be of a panel study type in which each data set consists of a sequence of observations on N>=2 independent and identically dis...
متن کاملBayes and empirical Bayes changepoint problems
We generalize the approach of Liu and Lawrence (1999) for multiple changepoint problems where the number of changepoints is unknown. The approach is based on dynamic programming recursion for efficient calculation of the marginal probability of the data with the hidden parameters integrated out. For the estimation of the hyperparameters, we propose to use Monte Carlo EM when training data are a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Communications for Statistical Applications and Methods
سال: 2013
ISSN: 2287-7843
DOI: 10.5351/csam.2013.20.4.321