A neglected aspect of the otherwise fairly well developed Bayesian analysis of cointegration is the point estimation of the cointegration space. It is pointed out here that, due to the well known non-identification of the cointegration vectors, the parameter space is not an inner product space and conventional Bayes estimators therefore stand without their usual decision theoretic foundation. W...

In this paper, several related estimation problems are addressed from a Bayesian point of view, and optimal estimators obtained for each them when some natural loss functions considered. The considered the regression curve, conditional distribution function, density, even itself. These posed in sufficiently general framework to cover continuous discrete, univariate multivariate, parametric nonp...

This paper derives the entropy of a generalized half-logistic distribution based on Type-II censored samples, obtains some entropy estimators by using Bayes estimators of an unknown parameter in the generalized half-logistic distribution based on Type-II censored samples and compares these estimators in terms of the mean squared error and the bias through Monte Carlo simulations.

This paper is the second in a series of two on the problem of estimating a function of a probability distribution from a finite set of samples of that distribution. In the first paper1, the Bayes estimator for a function of a probability distribution was introduced, the optimal properties of the Bayes estimator were discussed, and the Bayes and frequency-counts estimators for the Shannon entrop...

In this paper, the geometric distribution parameter is estimated under a type-I censoring scheme by means of Bayesian estimation approach. The Beta and Kumaraswamy informative priors, as well five loss functions are used for purpose. Expressions Bayes estimators risks derived Squared Error Loss Function (SELF), Quadratic (QLF), Precautionary (PLF), Simple Asymmetric (SAPLF), DeGroot (DLF) using...

Maximum likelihood and Bayes estimators of the parameters, survival function (SF) and hazard rate function (HRF) are obtained for the three-parameter exponentiated Burr type XII distribution when sample is available from type II censored scheme. Bayes estimators have been developed using the standard Bayes and MCMC methods under square error and LINEX loss functions, using informative type of p...

Estimation in truncated parameter space is one of the most important features in statistical inference, because the frequently used criterion of unbiasedness is useless, since no unbiased estimator exists in general. So, other optimally criteria such as admissibility and minimaxity have to be looked for among others. In this paper we consider a subclass of the exponential families of distributi...

Statistics) MODEL SELECTION, COVARIANCE SELECTION AND BAYES CLASSIFICATION VIA SHRINKAGE ESTIMATORS by

This paper is the second in a series of two on the problem of estimating a function of a probability distribution from a finite set of samples of that distribution. In the first paper1, the Bayes estimator for a function of a probability distribution was introduced, the optimal properties of the Bayes estimator were discussed, and the Bayes and frequency-counts estimators for the Shannon entrop...