2012•Journal of Statistical Computation and SimulationRequires access

EM algorithms for beta kernel distributions

Mahdi Teimouri, Saralees Nadarajah, Shou Hsing Shih

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.

About this research paper

What this paper is about

Why it matters

OpenAlex reports 6 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Key concepts: Mathematics, BETA (programming language), Beta distribution, Kernel (algebra), Algorithm, Applied mathematics, Statistics, Combinatorics