Multivariate Negative Binomial-Quasi Lindley Distribution for Correlated Count Data
Sirinapa Aryuyuen, Nikorn Saengngam, Unchalee Tonggumnead
Source record
Source: Crossref
Published: Dec 31, 2025
DOI: 10.37394/23206.2025.24.75
Open original source ↗Source abstract
In this paper, a multivariate version of the negative binomial-quasi Lindley (NB-QL) distribution is proposed, and some of the characteristics of the distribution are discussed. The bivariate NB-QL distribution is demonstrated as a special instance of the multivariate NB-QL distribution. This approach is suitable for use in any domain where overdispersion can be detected. The maximum likelihood estimation is used for estimating parameters through numerical optimization with R programming. A simulation to estimate parameters is illustrated. Furthermore, the empirical data detailing the frequency of faults occurring weekly in two feeders in Thailand are analyzed using univariate, bivariate, and conditional NB-QL distributions. The results indicate that the expected frequencies exhibit appropriate goodness of fit, suggesting that the proposed distribution can flexibly and appropriately model count data.
Evidence graph
No public relationships recorded yet.
Integrity note: This page is a factual metadata record created by deterministic ingestion. It is not a claim that the work moves a mathematical frontier or has been independently verified.