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Estimation of Generalized Inverted Exponential Distribution for Progressively Type I Interval Censored Samples

Yu-Hyung Lee, Suk-Bok Kang


This paper investigates the inference on the parameter estimation of generalized inverted exponential distribution based on progressively Type I interval censored samples. Distribution parameters are estimated using the maximum likelihood, midpoint approximation, EM algorithm, and average-point approximation methods, and their performance is compared using simulation results in terms of their mean squared error and bias for various censored samples.


Average-point method, EM algorithm, maximum likelihood estimator, Progressively Type I interval censoring.

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