A New Flexible Probability Model: Theory, Estimation and Modeling Bimodal Left Skewed Data

Autor:	Mohamed Aboraya, M. Masoom Ali, Haitham M. Yousof, Mohamed Ibrahim Mohamed
Rok vydání:	2022
Předmět:	Statistics and Probability Modeling and Simulation Management Science and Operations Research Statistics Probability and Uncertainty
Zdroj:	Pakistan Journal of Statistics and Operation Research. :437-463
ISSN:	2220-5810 1816-2711
DOI:	10.18187/pjsor.v18i2.3938
Popis:	In this work, we introduced a new three-parameter Nadarajah-Haghighi model. We derived explicit expressions for some of it statistical properties. The Farlie Gumbel Morgenstern, modified Farlie Gumbel Morgenstern, Clayton, Renyi and Ali-Mikhail-Haq copulas are used for deriving some bivariate type extensions. We consider maximum likelihood, Cramér-von-Mises, ordinary least squares, whighted least squares, Anderson Darling, right tail Anderson Darling and left tail Anderson Darling estimation procedures to estimate the unknown model parameters. Simulation study for comparing estimation methods is performed. An application for comparing methods as also presented. The maximum likelihood estimation method is the best method. However, the other methods performed well. Another application for comparing the competitive models is investigated.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::08804fe70248387e5fc98b1b64de13e7 https://doi.org/10.18187/pjsor.v18i2.3938 Zobrazit plný text záznamu