The present paper considers modified extension of the exponential distribution with three parameters. The main properties of this new distribution is studied, with special emphasis on its median, mode and moments function and some characteristics related to reliability studies. For Modifiedextension exponential distribution (MEXED) have been obtained the Bayes Estimators of scale and shape para...

The present paper considers modified extension of the exponential distribution with three parameters. The main properties of this new distribution is studied, with special emphasis on its median, mode and moments function and some characteristics related to reliability studies. For Modifiedextension exponential distribution (MEXED) have been obtained the Bayes Estimators of scale and shape para...

Let y = Aβ + ε, where y is an N × 1 vector of observations, β is a p× 1 vector of unknown regression coefficients, A is an N × p design matrix and ε is a spherically symmetric error term with unknown scale parameter σ. We consider estimation of β under general quadratic loss functions, and, in particular, extend the work of Strawderman [J. Amer. Statist. Assoc. 73 (1978) 623–627] and Casella [A...

The present paper considers modified extension of the exponential distribution with three parameters. The main properties of this new distribution is studied, with special emphasis on its median, mode and moments function and some characteristics related to reliability studies. For Modifiedextension exponential distribution (MEXED) have been obtained the Bayes Estimators of scale and shape para...

Empirical Bayes' (EB) estimation is a widely used procedure to calculate teacher value-added. It is primarily viewed as a way to make imprecise estimates more reliable. In this paper we review the theory of EB estimation and use simulated data to study its ability to properly rank teachers. We compare the performance of EB estimators with that of other widely used value-added estimators under d...

Let X ∼ Np(θ, σIp) and W ∼ σχm, where both θ and σ are unknown, and X is independent of W . Optimal estimation of θ with unknown σ is a fundamental issue in applications but basic theoretical issues remain open. We consider estimation of θ under squared error loss. We develop sufficient conditions for prior density functions such that the corresponding generalized Bayes estimators for θ are adm...

Estimation procedures for nonstationary Markov chains appear to be relatively sparse. This work introduces empirical  Bayes estimators  for the transition probability  matrix of a finite nonstationary  Markov chain. The data are assumed to be of  a panel study type in which each data set consists of a sequence of observations on N>=2 independent and identically dis...

Of those things that can be estimated well in an inverse problem, which is best to estimate? Backus–Gilbert resolution theory answers a version of this question for linear (or linearized) inverse problems in Hilbert spaces with additive zero-mean errors with known, finite covariance, and no constraints on the unknown other than the data. This paper generalizes resolution: it defines the resolut...

Consider the problem of estimating a multivariate normal mean with a known variance matrix, which is not necessarily proportional to the identity matrix. The coordinates are shrunk directly in proportion to their variances in Efron and Morris’ (J. Amer. Statist. Assoc. 68 (1973) 117–130) empirical Bayes approach, whereas inversely in proportion to their variances in Berger’s (Ann. Statist. 4 (1...

In this work the analysis of interval-censored data, with Weibull distribution as the underlying lifetime distribution has been considered. It is assumed that censoring mechanism is independent and non-informative. As expected, the maximum likelihood estimators cannot be obtained in closed form. In our simulation experiments it is observed that the Newton-Raphson method may not converge many ti...