  The paper addresses the problem of estimation of the model parameters of the
logistic exponential distribution based on progressive type-I hybrid censored
sample. The maximum likelihood estimates are obtained and computed numerically
using Newton-Raphson method. Further, the Bayes estimates are derived under
squared error, LINEX and generalized entropy loss functions. Two types
(independent and bivariate) of prior distributions are considered for the
purpose of Bayesian estimation. It is seen that the Bayes estimates are not of
explicit forms.Thus, Lindley's approximation technique is employed to get
approximate Bayes estimates. Interval estimates of the parameters based on
normal approximate of the maximum likelihood estimates and normal approximation
of the log-transformed maximum likelihood estimates are constructed. The
highest posterior density credible intervals are obtained by using the
importance sampling method. Furthermore, numerical computations are reported to
review some of the results obtained in the paper. A real life dataset is
considered for the purpose of illustrations.
