The inverse Weibull model was developed by Erto [10]. In practice, the unknown parameters of the appropriate inverse Weibull density are not known and must be estimated from a random sample. Estimation of its parameters has been approached in the literature by various techniques, because a standard maximum likelihood estimate does not exist. To estimate the unknown parameters of the three-param...

In this paper we consider the Bayesian inference of the unknown parameters of the progressively censored competing risks data, when the lifetime distributions are Weibull. It is assumed that the latent cause of failures have independent Weibull distributions with the common shape parameter, but different scale parameters. In this article, it is assumed that the shape parameter has a log-concave...

Abstract. In this paper we develop Maximum Likelihood (ML) and Improved Analytical (IA) numerical algorithms to estimate parameters of the Weibull distribution, namely, location, scale and shape parameters, using order statistics of a noncensored sample. Since ML method leads to multiextremal numerical problem we establish conditions to localize extremes of the ML function, which enables us to ...