The concept of generalized order statistics is a distribution theoretical set-up, which contains a variety of models for ordered data as particular cases, such as common order statistics, sequential order statistics, progressively type-II censored order statistics, record values, kth record...

Predictive recursion (PR) is a fast stochastic algorithm for nonparametric estimation of mixing distributions in mixture models. It is known that the PR estimates of both the mixing and mixture densities are consistent under fairly mild conditions, but currently very little is known about the...

Hypothesis testing using Bayes factors (BFs) is known not to be well defined under the improper prior. In the context of latent variable models, an additional problem with BFs is that they are difficult to compute. In this paper, a new Bayesian method, based on the decision theory and the EM...

The aim of this work is to provide some characterization properties of the log-normal distribution with the help of divergence measures between a probability density function f and its r-size weighted counterpart fr. The characterization can be expressed in terms the Kullback–Leibler, the...

Hypothesis testing using Bayes factors (BFs) is known not to be well dened under the improper prior. In the context of latent variable models, an additional problem with BFs is that they are difficult to compute. In this paper, a new Bayesian method, based on decision theory and the EM...