  The exponential and the Lomax distributions are widely used in life testing
experiments in mixture models. A mixture model of exponential distribution and
Lomax distribution is proposed. Parameters of the proposed model are estimated
using classical and Bayesian procedures under type-I right censoring.
Expressions for Bayes estimators are derived assuming noninformative (uniform
and Jeffreys) priors under symmetric and asymmetric loss functions. Posterior
predictive distributions of a future observation are derived and predictive
estimates are obtained. Extensive Monte Carlo simulations are carried out to
investigate performance of the estimators in terms of sample sizes, censoring
times and mixing proportions. The analysis of mixture model is carried out
using a data set of lifetime of transmitter receivers. Interesting properties
of estimators are observed and discussed.

Methodology