Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1147630 | Journal of Statistical Planning and Inference | 2011 | 10 Pages |
Abstract
In this paper, and based on a progressive type-II censored sample from the generalized Rayleigh (GR) distribution, we consider the problem of estimating the model parameters and predicting the unobserved removed data. Maximum likelihood and Bayesian approaches are used to estimate the scale and shape parameters. The Gibbs and Metropolis samplers are used to predict the life lengths of the removed units in multiple stages of the progressively censored sample. Artificial and real data analyses have been performed for illustrative purposes.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Mohammad Z. Raqab, Mohamed T. Madi,