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Abstract
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The structure of the record ranked set sampling scheme is based on the idea of the ordinary ranked set sampling, which is a statistical method for data collection that can be viewed as a generalization of the simple random sampling. Based on the upper record ranked set sampling, this paper develops methods to estimate of the parameters of the generalized inverted exponential distribution. First, we derive the maximum likelihood estimators (MLEs) of the parameters and the expected Fisher information matrix. Next, we obtain the Bayesian estimators of the unknown parameters of the generalized inverted exponential distribution under the symmetric squared error loss function with the help of upper record ranked set sampling. These Bayesian estimators are evaluated by using Lindley’s approximation method and the importance sampling procedure. Besides, the importance sampling procedure is used to compute the highest posterior density credible intervals. Finally, Monte Carlo simulations are performed to compare the performances of the proposed methods of estimation and the daily heat degree real data is analyzed, to illustrate the findings.
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