Abstract
Finite mixture models provide a flexible tool for handling heterogeneous data. This paper
introduces a new mixture model which is the mixture of Lindley and lognormal distributions
(MLLND). First, the model is formulated, and some of its statistical properties are
studied. Next, maximum likelihood estimation of the parameters of the model is considered,
and the performance of the estimators of the parameters of the proposed models is
evaluated via simulation. Also, the flexibility of the proposed mixture distribution is
demonstrated by showing its superiority to fit a well-known real data set of 128 bladder
cancer patients compared to several mixture and nonmixture distributions. The Kolmogorov
Smirnov test and some information criteria are used to compare the fitted models to the
real dataset. Finally, the results are verified using several graphical methods.