Non-parametric maximum likelihood estimators of relative risk have been proposed as an alternative to empirical Bayes or full Bayes approaches to disease mapping. They have the advantage of being relatively simple, the EM algorithm assures convergence and area classi5cation is straightforward. However, they do not take into account spatial autocorrelation and have higher mean square error when ...

We study the properties of variational Bayes approximations for exponential family models with missing values. It is shown that the iterative algorithm for obtaining the variational Bayesian estimator converges locally to the true value with probability 1 as the sample size becomes indefinitely large. Moreover, the variational posterior distribution is proved to be asymptotically normal.

We study the properties of variational Bayes approximations for exponential family models with missing values. It is shown that the iterative algorithm for obtaining the variational Bayesian estimator converges locally to the true value with probability 1 as the sample size becomes indefinitely large. Moreover, the variational posterior distribution is proved to be asymptotically normal.

Hall’s recent derivation of an exact uncertainty relation [Phys. Rev. A64, 052103 (2001)] is revisited. It is found that the Bayes estimator of an observable between preand postselection equals the real part of the weak value. The quadratic loss function equals the expectation of the squared imaginary part of the weak value.

We define a new centroid estimator for text classification based on the KLdivergence of the classes. The score favors documents that have a similar distribution in documents of the same class but different distributions in documents of different classes. Experiments on several standard data sets indicate that the new method outperforms better than traditional Naive Bayes classifier, especially ...

Exact expressions for single and product moments of generalized order statistics are derived when the underlying population is assumed to have a Rayleigh distribution. Bayesian estimators and highest posterior density (HPD) credible intervals are obtained for the scale parameter and reliability function based on generalized order statistics. We also derive the Bayes predictive estimator and HPD...

In certain auction, search, and related models, the boundary of the support of the observed data depends on some of the parameters of interest. For such nonregular models, standard asymptotic distribution theory does not apply. Previous work has focused on characterizing the nonstandard limiting distributions of particular estimators in these models. In contrast, we study the problem of constru...

In certain auction, search, and related models, the boundary of the support of the observed data depends on some of the parameters of interest. For such nonregular models, standard asymptotic distribution theory does not apply. Previous work has focused on characterizing the nonstandard limiting distributions of particular estimators in these models. In contrast, we study the problem of constru...

Many variables of interest in business and agricultural surveys have skewed distributions. An example from the National Agricultural Statistics Service is the acres harvested for a particular crop. We investigate small area estimation methods for skewed data under the assumption that a lognormal model is a reasonable approximation for the distribution of the response given covariates. Empirical...