Abstract In this paper, we consider Kumaraswamy-G distributions and derive a Uniformly Minimum Variance Unbiased Estimator (UMVUE) Maximum Likelihood (MLE) of the two measures reliability, namely R ( t ) = P X > Y under Type II censoring scheme sampling Bartholomew (1963). We also develop interval estimates reliability measures. A comparative study different methods point estimation has been...

In this paper, we consider the estimation of the unknown parameter of the scaled logistic distribution on the basis of record values. The maximum likelihood method does not provide an explicit estimator for the scale parameter. In this article, we present a simple method of deriving an explicit estimator by approximating the likelihood function. Bayes estimator is obtained using importance samp...

let be a random sample from a normal distribution with unknown mean and known variance the usual estimator of the mean, i.e., sample mean is the maximum likelihood estimator which under squared error loss function is minimax and admissible estimator. in many practical situations, is known in advance to lie in an interval, say for some in this case, the maximum likelihood estimator changes and d...

CONTENTS 1. Introduction 2. Image and blur models 3. Maximum likelihood (ML) parameter identification 3.1. Formulation 3.2. Constraints on the unknown parameters 4. ML parameter identification via the expectation-maximization (EM) algorithm 4.1. The EM algorithm in the linear Gaussian case 4.2. Choices of complete data 4.2.1. {x,y} as the complete data 4.2.2. {x,v} as the complete data Abstract...

Abstract: This paper presents the optimal design for accelerated life testing (ALT) experiments when step-stress plans with Type I censoring are performed. We adopt a generalized Khamis-Higgins model for the effect of changing stress levels. It is assumed that the lifetime of a test unit follows a Weibull distribution, and both its shape and scale parameters are functions of the stress level. T...

The problem of abrupt change detection has received much attention in the literature. The Neyman—Pearson detector can be derived and yields the well-known CUSUM algorithm, when the abrupt change is contaminated by an additive noise. However, a multiplicative noise has been observed in many signal processing applications. These applications include radar, sonar, communication and image processin...

In this paper, we focus on the parametric inference based Tampered Random Variable (TRV) model for simple step-stress life testing (SSLT) using Type-II censored data. The baseline lifetime of experimental units, under normal stress conditions, follows Gumbel distribution with $\alpha$ and $\lambda$ being shape scale parameters, respectively. Maximum likelihood estimator (MLE) Bayes parameters a...

The maximum likelihood estimator (MLE) of the fractional difference parameter in the Gaussian ARFIMA(0, d, 0) model is well known to be asymptotically N(0, 6/π). This paper develops a second order asymptotic expansion to the distribution of this statistic. The correction term for the density is shown to be independent of d, so that the MLE is second order pivotal for d. This feature of the MLE ...

In 12], Witkin proposed a maximum likelihood (ML) estimator of surface orientation based on the observed directional bias of projected texture elements. However, a drawback of this procedure is that the estimate is only deened indirectly in terms of a set of non-linear equations. In this paper we propose an alternative method, which allows an estimate of the surface orientation to be computed d...

This paper considers generalized method of moments (GMM) and sequential GMM (SGMM) estimation dynamic short panel data models. The efficient motivated from the quasi maximum likelihood (QML) can avoid use many instrument variables (IV) for estimation. It be asymptotically as estimators (MLE) when disturbances are normal, more than QML not normal. SGMM, which also incorporates IVs, generalizes m...