Kundu, D. and Howlader, H. (2010) Bayesian Inference and Prediction of the Inverse Weibull Distribution for Type-II Censored Data. Computational Statistics & Data Analysis, 54, 1547-1558.
http://dx.doi.org/10.1016/j.csda.2010.01.003

has been cited by the following article:

• TITLE: Comparison of the Bayesian Methods on Interval-Censored Data for Weibull Distribution

  AUTHORS: Al Omari Mohammed Ahmed

  KEYWORDS: Weibull Distribution, Bayesian Method, Interval Censored, Metropolis-Hastings Algorithm, Lindley’s Approximation

  JOURNAL NAME: Open Journal of Statistics, Vol.4 No.8, September 17, 2014

  ABSTRACT: This study considers the estimation of Maximum Likelihood Estimator and the Bayesian Estimator of the Weibull distribution with interval-censored data. The Bayesian estimation can’t be used to solve the parameters analytically and therefore Markov Chain Monte Carlo is used, where the full conditional distribution for the scale and shape parameters are obtained via Metropolis-Hastings algorithm. Also Lindley’s approximation is used. The two methods are compared to maximum likelihood counterparts and the comparisons are made with respect to the mean square error (MSE) to determine the best for estimating of the scale and shape parameters.