  Kundu and Gupta (2007, Metrika, 65, 159 - 170) provided the analysis of
Type-I hybrid censored competing risks data, when the lifetime distribution of
the competing causes of failures follow exponential distribution. In this paper
we consider the analysis of Type-II hybrid censored competing risks data. It is
assumed that latent lifetime distributions of the competing causes of failures
follow independent exponential distributions with different scale parameters.
It is observed that the maximum likelihood estimators of the unknown parameters
do not always exist. We propose the modified estimators of the scale
parameters, which coincide with the corresponding maximum likelihood estimators
when they exist, and asymptotically they are equivalent. We obtain the exact
distribution of the proposed estimators. Using the exact distributions of the
proposed estimators, associated confidence intervals are obtained. The
asymptotic and bootstrap confidence intervals of the unknown parameters are
also provided. Further, Bayesian inference of some unknown parametric functions
under a very flexible Beta-Gamma prior is considered. Bayes estimators and
associated credible intervals of the unknown parameters are obtained using
Monte Carlo method. Extensive Monte Carlo simulations are performed to see the
effectiveness of the proposed estimators and one real data set has been
analyzed for the illustrative purposes. It is observed that the proposed model
and the method work quite well for this data set.
