a two-factor experiment with interaction between factors wherein observations follow an inverse gaussian model is considered. analysis of the experiment is approached via an empirical bayes procedure. the conjugate family of prior distributions is considered. bayes and empirical bayes estimators are derived. application of the procedure is illustrated on a data set, which has previously been an...

the empirical bayes estimators of treatment effects in a factorial experiment were derived and their asymptotic properties were explored. it was shown that they were asymptotically optimal and the estimator of the scale parameter had a limiting gamma distribution while the estimators of the factor effects had a limiting multivariate normal distribution. a bootstrap analysis was performed to ill...

this article examines statistical inference for  where and are independent but not identically distributed pareto of the first kind (pareto (i)) random variables with same scale parameter but different shape parameters. the maximum likelihood, uniformly minimum variance unbiased and bayes estimators with gamma prior are used for this purpose. simulation studies which compare the estimators are ...

A two-factor experiment with interaction between factors wherein observations follow an Inverse Gaussian model is considered. Analysis of the experiment is approached via an empirical Bayes procedure. The conjugate family of prior distributions is considered. Bayes and empirical Bayes estimators are derived. Application of the procedure is illustrated on a data set, which has previously been an...

Small area estimation has received a lot of attention in recent years due to growing demand for reliable small area statistics. Traditional area-specific estimators may not provide adequate precision because sample sizes in small areas are seldom large enough. This makes it necessary to employ indirect estimators based on linking models. Basic area level and unit level models have been extensiv...

in this paper, a bayesian approach is proposed for shift point detection in an inverse gaussian distribution. in this study, the mean parameter of inverse gaussian distribution is assumed to be constant and shift points in shape parameter is considered. first the posterior distribution of shape parameter is obtained. then the bayes estimators are derived under a class of priors and using variou...

an estimation problem of the mean µ of an inverse gaussian distribution ig(µ, c µ) with known coefficient of variation c is treated as a decision problem with entropy loss function. a class of bayes estimators is constructed, and shown to include mrse estimator as its closure. two important members of this class can easily be computed using continued fractions

We consider the problem of estimating the scale parameter &beta of a rescaled F-distribution when &beta has a lower bounded constraint of the form &beta&gea, under the entropy loss function. An admissible minimax estimator of the scale parameter &beta, which is the pointwise limit of a sequence of Bayes estimators, is given. Also in the class of truncated linear estimators, the admissible estim...

Recently two-parameter generalized exponential distribution has been introduced by the authors. In this paper we consider the Bayes estimators of the unknown parameters under the assumptions of gamma priors on both the shape and scale parameters. The Bayes estimators can not be obtained in explicit forms. Approximate Bayes estimators are computed using the idea of Lindley. We also propose Gibbs...