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Research Article Open access CC BY 4.0

Estimation of Logistic Parameters Using a Fuzzy Least-squares Method and Different Types of Moments

Hegazy M. Zaher, Ahmed A. El-sheik, Noura A. T. Abu El-Magd

Journal of Scientific Research and Reports · pp. 514–532 · Published 5 Nov 2014

10.9734/JSRR/2015/12483

Abstract

The main attention of this paper is to deduce the estimators of the parameters of the Logistic distribution using five estimating methods, namely, the fuzzy least-squares method, the LQ-moments (linear quantile moments) with three cases (trimean, median and Gastwirth), TL-moments (trimmed linear moments) with different individual cases, L-moments (linear moments) and the maximum likelihood method. Also, a comparison between the performances of these estimators using simulations is given. According to these comparisons, it is shown that the proposed fuzzy least-squares algorithm is preferred for large sample size.

Logistic distribution fuzzy least-squares maximum likelihood TL-moments L-moments LL-moments LH-moments LQ-moments simulations

References (13)

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Cited by 2

Using different types of moments to estimate (L-moments, T L-moments and LQ-moments)

Fatimah Assim Mahdi · AIP Conference Proceedings · 2023

Showing 1 of 2 known citations — external sources report more than can currently be individually listed.

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