In this paper, we discuss the statistical inference on the unknown parameters and reliability function of type-II extreme value (EVII) distribution when the observed data are progressively type-II censored. By applying EM algorithm, we obtain maximum likelihood estimates (MLEs). We also suggest approximate maximum likelihood estimators (AMLEs), which have explicit expressions. We provide Bayes ...

HERE WE PRESENT the likelihood function used to estimate the parameters of the demand model. The model can be thought of as a system of four “standard” equations: (i) a tobit down payment equation (with censoring at the minimum down), (ii) a probit purchase equation, (iii) a tobit repayment equation (with censoring at full payment or at the end of our sample), and (iv) a linear price negotiatio...

The kernel smoothed Nelson–Aalen estimator has been well investigated, but is unsuitable when some of the censoring indicators are missing. A representation introduced by Dikta, however, facilitates hazard estimation when there are missing censoring indicators. In this article, we investigate (i) a kernel smoothed semiparametric hazard estimator and (ii) a kernel smoothed “pre-smoothed” Nelson ...

Abstract: This paper considers the estimation of parameters based on a progressively type-I interval-censored data from a mixed generalized exponential distribution. The maximum likelihood estimation is used but an analytic form cannot be obtained. The EM algorithm is applied to obtain the maximum likelihood estimates. The performance of the estimates is judged by a simulating study and a real ...

In this paper it will show how unknown density and distribution functions can be modeled semi-nonparametrically via orthonormal series expansions, and how to estimate semi-nonparametric (SNP) models via a sieve estimation approach. As an application I will focus on the mixed proportional hazard (MPH) model with fixed right censoring and unspecified mixing distribution and baseline hazard. I wil...

The stress–strength analysis is investigated for a multicomponent system, where all strength variables of components follow generalized exponential distribution and are subject to the distributed stress. estimation methods maximum likelihood Bayesian utilized infer system reliability. For method, informative non-informative priors combined with three loss functions considered. Because computati...

In this paper we study the estimation of a quantile function based on left truncated and right censored data by the kernel smoothing method. Asymptotic normality and a Berry-Esseen type bound for the kernel quantile estimator are derived. Monte Carlo studies are conducted to compare the proposed estimator with the PL-quantile estimator.

In this study, we consider a censoring scheme called progressive type-II censoring. Under this scheme, n units are placed on a test at time zero, with m failures to be observed. When the first failure is observed, r1 of the surviving units are randomly selected and removed. At the second observed failure, r2 of the surviving units are randomly selected and removed. This experiment stops at the ...