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On Characterizations of Erlang Truncated Exponential Distribution through Generalized Order Statistics with Applications to Statistical Prediction Problem |
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PP: 865-874 |
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doi:10.18576/jsap/140624
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Author(s) |
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Imtiyaz A. Shah,
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Abstract |
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| Erlang Truncated Exponential Distributions are characterized by distributional properties of generalized order statistics. These characterizations include known results for ordinary order statistics based on two non-adjacent m-generalized order statistics coming from two independent Erlang truncated exponential distributions. Using this method and compared with an efficient recent method given by [33], three examples of real lifetime data-sets are analyzed by that deals with non-random samples. Such type of examples predicts the accumulative new cases per million foe infection of the new COVID-19. Corollaries for Pareto and power function distributions are also derived.
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