Logistic Nadarajah-Haghighi distribution: Estimation and properties | ||||
| المجلة العلمية للدراسات والبØوث المالية والتجارية | ||||
| Volume 5, Issue 2 - Serial Number 1, July 2024, Page 553-575 PDF (2 MB) | ||||
| Document Type: المقالة الأصلية | ||||
| DOI: 10.21608/cfdj.2024.268012.1904 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Ù…Øمد عبد القادر  1; tamer Ali2
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| 1جامعة الأزهر کلية التجارة | ||||
| 2faculty of commerce, Alazhar university | ||||
| Abstract | ||||
| This study explores four estimation methods for the Logistic Nadarajah-Haghighi (LNH) distribution, utilizing complete sampling and Maximum Likelihood Estimation (MLE) based on two censoring types: | & ||. The paper assesses the squared bias and variances of these estimates through Monte Carlo simulations. Additionally, it provides insights into ordinary moments, the quintile function, mean residual life, and Renyi entropy. The research builds upon previous work in this domain. Ziyad (2017) [21] focused on statistical inferences for the exponentiated Nadarajah-Haghighi (ENH) distribution with progressively type-II censoring. Cícero (2018a) [2] proposed the beta Nadarajah-Haghighi distribution as a generalization. Hilany (2018b) [4] derived ordinary differential equations (ODE) for the probability functions of the Marshall-Olkin Nadarajah-Haghighi distribution using differentiation. Morad (2018c) [15] introduced the Extended Exponentiated-Nadarajah-Haghighi (EENH) distribution as a four-parameter model. Hisham (2019a) [5] proposed the Burr X Nadarajah-Haghighi distribution, expanding the original distribution. Ms.Sana (2019b) [16] delved into maximum likelihood and Bayesian estimation for the two unknown parameters of the Nadarajah and Haghighi distribution. Fernando (2020a) [3] presented the logistic Nadarajah–Haghighi distribution, a three-parameter model, and proposed a parametric regression model. Marija (2020b) [12] estimated shape and scale parameters of Nadarajah-Haghighi based on simple random samples (SRS) and ranked set sampling (RSS). Sanku (2021) [20] presented estimation methods for parameters and acceleration factor in Nadarajah–Haghighi distribution based on constant-stress partially accelerated life tests. Almarashi (2022a) [1] focused on maximum likelihood and Bayesian estimation methods for the unknown parameters, reliability, and hazard rate functions of the Nadarajah–Haghighi (NH) distribution, | ||||
| Keywords | ||||
| Logistic Nadarajah-Haghighi; Renyi entropy; mean residual life; Progressive Type-II Censoring | ||||
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