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Generalized inverted exponential distribution under hybrid censoring |
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| Affiliation: | 1. Department of Statistics, St. Anthony’s College, Shillong, Pin-793001, India;2. SQC & OR Unit, Indian Statistical Institute, 203 B.T. Road, Kolkata, Pin 700108, India;1. School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang, 471023, China;2. School of Statistics, Renmin University of China, Beijing, 100872, China;1. Department of Statistics, St. Anthony’s College, Shillong-793001, Meghalaya, India;2. Department of Mathematics, Indian Institute of Technology Patna, Bihta-801103, India;3. Department of Statistics, University of Mazandaran, Babolsar, Iran |
| Abstract: | The hybrid censoring scheme is a mixture of Type-I and Type-II censoring schemes. Based on hybrid censored samples, we first derive the maximum likelihood estimators of the unknown parameters and the expected Fisher’s information matrix of the generalized inverted exponential distribution (GIED). Monte Carlo simulations are performed to study the performance of the maximum likelihood estimators. Next we consider Bayes estimation under the squared error loss function. These Bayes estimates are evaluated by applying Lindley’s approximation method, the importance sampling procedure and Metropolis–Hastings algorithm. The importance sampling technique is used to compute the highest posterior density credible intervals. Two data sets are analyzed for illustrative purposes. Finally, we discuss a method of obtaining the optimum hybrid censoring scheme. |
| Keywords: | Type-I and type-II censoring schemes Fisher information matrix Loss function Lindley’s approximation Importance sampling Optimum censoring scheme |
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