EM algorithms for beta kernel distributions

Abstract

The EM algorithm is employed to compute maximum-likelihood estimates for beta kernel distributions. Estimation is considered under two censoring schemes: the progressive Type-I censoring and progressive Type-II right censoring schemes. As an application, the EM algorithm is executed to obtain maximum-likelihood estimates for the beta Weibull distribution under the two censoring schemes. A simulation study and two real data sets are used to show the efficiency of the EM algorithm.

Keywords:

• beta kernel distributions
• censoring schemes
• EM algorithm

Acknowledgements

The authors thank the editor and the referee for careful reading and for their comments which greatly improved the paper.