| Title: |
On the Kumaraswamy Pseudo-Lindley distribution : statistical properties, extremal characterization and record values. |
| Authors: |
Diallo, Moumouni; Ngom, Modou; Fall, Adja Mbarka; Lo, Gane Samb |
| Source: |
Afrika Statistika; Jul2022, Vol. 17 Issue 3, p3259-3291, 33p |
| Subject Terms: |
STATISTICS; QUANTILES; DESCRIPTIVE statistics; MONTE Carlo method; MATHEMATICS |
| Abstract (English): |
The Pseudo-Lindley distribution is generalized in this paper by using the Kumaraswamy-G distribution developed by Cordeiro et al. (2010a). By fusing the Pseudo-Lindley distribution in the Kumaraswamy generator of distribution, we present a new unique four parameters of continuous model of distribution titled the Kumaraswamy Pseudo-Lindley distribution (Kum-PL). The moments and related measures, moment generating function, order statistic, uniform quantile and extremal quantile function are all carefully examined as basic statistical aspects of the new distribution. Moreover, the extremal characterizations and record values of the new model are investigated.The proposed distribution parameters were evaluated using the maximum likelihood procedures. The stability of the parameter estimations is explored using a Monte Carlo simulation study. [ABSTRACT FROM AUTHOR] |
| Abstract (French): |
La distribution pseudo-Lindley est généralisée dans cet article en utilisant la distribution Kumaraswamy-G développée par Cordeiro et al. (2010a). En fusionnant la Distribution pseudo-Lindley dans le générateur de distribution de Kumaraswamy, nous présentons un nouveau modèle unique à quatre paramètres de distribution continue intitulé la distribution Ku- maraswamy Pseudo-Lindley (Kum-PL). Les moments et mesures associées, la fonc- tion génératrice des moments, la statistique d'ordre, le quantile uniforme et la fonction quantile extrême sont tous soigneusement abordés comme des aspects statistiques de base de la nouvelle distribution. De plus, la caractérisation des extrêmes et les records du nouveau modèle sont étudiés. Les paramètres de la dis- tribution proposée ont été estimés en utilisant le maximum de vraisemblance. La stabilité des estimateurs des paramètres est explorée à láide dúne étude de simu- lation de Monte Carlo [ABSTRACT FROM AUTHOR] |
| : |
Copyright of Afrika Statistika is the property of Statistics & Probability African Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Complementary Index |