A competing risks model is analysed based on improved adaptive type-II progressive

censored sample (IAT-II PCS). Two independent competing causes of failures are considered.

It is assumed that lifetimes of the competing causes of failure follow exponential distributions

with different means. Maximum likelihood estimators (MLEs) for the unknown model

parameters are obtained. Using asymptotic normality property of MLE, the asymptotic

confidence intervals are constructed. Existence and uniqueness properties of the MLEs are

studied. The Bayes estimators are obtained under symmetric and asymmetric loss functions

with non-informative and informative priors. For informative priors, independent gamma

distributions are considered. Highest posterior density (HPD) credible intervals are obtained.

A Monte Carlo simulation study is carried out to compare performance of the established

estimates.