A Novel Zero-Truncated Katz Distribution by the Lagrange Expansion of the Second Kind with Associated Inferences

Autor: Damodaran Santhamani Shibu, Christophe Chesneau, Mohanan Monisha, Radhakumari Maya, Muhammed Rasheed Irshad
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Analytics, Vol 2, Iss 2, Pp 463-484 (2023)
Druh dokumentu: article
ISSN: 2813-2203
DOI: 10.3390/analytics2020026
Popis: In this article, the Lagrange expansion of the second kind is used to generate a novel zero-truncated Katz distribution; we refer to it as the Lagrangian zero-truncated Katz distribution (LZTKD). Notably, the zero-truncated Katz distribution is a special case of this distribution. Along with the closed form expression of all its statistical characteristics, the LZTKD is proven to provide an adequate model for both underdispersed and overdispersed zero-truncated count datasets. Specifically, we show that the associated hazard rate function has increasing, decreasing, bathtub, or upside-down bathtub shapes. Moreover, we demonstrate that the LZTKD belongs to the Lagrangian distribution of the first kind. Then, applications of the LZTKD in statistical scenarios are explored. The unknown parameters are estimated using the well-reputed method of the maximum likelihood. In addition, the generalized likelihood ratio test procedure is applied to test the significance of the additional parameter. In order to evaluate the performance of the maximum likelihood estimates, simulation studies are also conducted. The use of real-life datasets further highlights the relevance and applicability of the proposed model.
Databáze: Directory of Open Access Journals