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Zamanzade, E., Mahdizadeh, M. and Samawi, H.M. (2020) Efficient Estimation of Cumulative Distribution Function Using Moving Extreme Ranked Set Sampling with Application to Reliability. AStA Advances in Statistical Analysis, 104, 485-502.
https://doi.org/10.1007/s10182-020-00368-3

has been cited by the following article:

• TITLE: Uniformly Minimum-Variance Unbiased Estimator (UMVUE) for the Gamma Cumulative Distribution Function with Known and Integer Scale Parameter

  AUTHORS: Jessica Kubrusly

  KEYWORDS: UMVUE, Cumulative Distribution Estimates, Gamma Distribution, Erlang Distribution, Lehmann-Scheffeé Theorem, Rao-Blackwell Theorem

  JOURNAL NAME: Open Journal of Statistics, Vol.12 No.2, April 2, 2022

  ABSTRACT: Uniformly minimum-variance unbiased estimator (UMVUE) for the gamma cumulative distribution function with known and integer scale parameter. This paper applies Rao-Blackwell and Lehmann-Scheffeé Theorems to deduce the uniformly minimum-variance unbiased estimator (UMVUE) for the gamma cumulative distribution function with known and integer scale parameters. The paper closes with an example comparing the empirical distribution function with the UMVUE estimates.