Inference for generalized inverse exponential distribution based on generalized hybrid Progressive censored data and its application to plasma spray data

In many applied research, the researcher does not have access to all the data for some reasons such as time and cost constraints. So, the statistical inference based on the available data is important. In this paper, estimation of unknown parameters of a generalized inverted exponential distribution is studied under generalized Type II progressive hybrid censoring. The maximum likelihood estimators and their existence and uniqueness are investigated. Based on the Bayesian approach, the estimators of the shape and scale parameters are derived under squared error loss function. Since closed - form expressions for the Bayes estimators cannot be obtained, we use Lindley’s approximation and important sampling procedure for obtaining them. Simulation study for comparing the different classical and Bayesian estimations is presented. Finally, two real data sets contain oblique impact of micro droplets onto surface in plasma spray coating process and repair time for a communication transmitter are analyzed for illustration purposes.