Abstract
In this paper, the identifiability property has been studied for a suggested truncated type-I generalized logistic mixture model which is denoted by
TTIGL
. A suggested form of the
EM
algorithm has been applied on type-II progressive censored samples to obtain the maximum likelihood estimates
MLE
′
s
of the parameters, survival function
SF
, and hazard rate function
HRF
of the studied mixture model. Monte Carlo simulation algorithm has been applied to study the behavior of the mean squares errors
MSE
′
s
of the estimates. Also, a comparative study is conducted between the suggested
EM
algorithm and the ordinary algorithm of maximizing the likelihood function, which depends on the differentiation of the log likelihood function. The results of this paper have been applied on a real dataset as an application.