In this paper, the Bayesian analysis of inverse Rayleigh distribution has been considered under singly and doubly type II censored data. The Bayes estimators and corresponding risks have been derived under the assumption of non-informative priors and using symmetric and asymmetric loss functions. The credible intervals have been constructed under the assumption of non-informat ive prio rs. The ...

The aim of this article is to study the estimation of the parameter of ЭРланга distribution based on complete samples. The Bayes estimators of the parameter of ЭРланга distribution are obtained under three different loss functions, namely, weighted square error loss, squared log error loss and entropy loss functions by using conjugate prior inverse Gamma distribution. Then the minimax estimator...

Motivated by recent developments in manifold-valued regression we propose a family of nonparametric kernel-smoothing estimators with metric-space valued output including several robust versions. Depending on the choice of the output space and the metric the estimator reduces to partially well-known procedures for multi-class classification, multivariate regression in Euclidean space, regression...

The possibility of employing explicitly defined functions of the observations as estimators of parametric functions in nonlinear regression analysis is explored. A general theory of best average mean square error estimation leading to explicit estimators is set forth. Such estimators are given a Bayesian interpretation as Fourier expansions of the estimator which minimizes expected posterior sq...

Exchangeable random partition processes are the basis for Bayesian approaches to statistical inference in large alphabet settings. On the other hand, the notion of the pattern of a sequence provides a framework for data compression in large alphabet scenarios. Because data compression and parameter estimation are intimately related, we study the redundancy of Bayes estimators coming from Poisso...

We consider a model in which there are m products and for each i=1,...,m, there are ni observations of the service times associated with the th i product. Assuming the service times associated with the th i product follow an exponential distribution with parameter i θ , and i θ 's are independent random variables with a common gamma distribution, with unknown parameters α and β , we provide two...

The use of the Pareto distribution as a model for various socio-economic phenomena dates back to the late nineteenth century. In this paper, after some necessary preliminary results we deal with Bayes estimation of some of the parameters of interest under an asymmetric LINEX loss function, using suitable choice of priors when the scale parameter is known and unknown. Results of a Monte C...

In this paper, by considering an $$M|M|1|\infty$$ queueing model, Bayes estimators of traffic intensity and system performance measures are discussed under (i) squared error loss function (SELF) (ii) entropy (ELF) (iii) LINEX with Beta prior. Further, minimum posterior risk associated obtained SELF. The the model compared Uniformly Minimum Variance Unbiased Estimators (UMVUEs) through simulation.

We propose an adaptive shrinkage estimator for use in regression problems charaterized by many predictors, such as wavelet estimation. Adaptive estimators perform well over a variety of circumstances, such as regression models in which few, some or many coefficients are zero. Our estimator, PolyShrink, adaptively varies the amount of shrinkage to suit the estimation task. Whereas hard threshold...

Classical approaches to estimating the rate of occurrence of events perform poorly when data are few. Maximum Likelihood Estimators result in overly optimistic point estimates of zero for situations where there have been no events. Alternative empirical based approaches have been proposed based on median estimators or noninformative prior distributions. While these alternatives offer an improve...