@Article{CMR-38-1,
author = {Christophe, Chesneau and S., Hassan, Bakouch and Yunus, Akdoğan and Karakaya, Kadir},
title = {The Binomial-Discrete Poisson-Lindley Model: Modeling and Applications to Count Regression},
journal = {Communications in Mathematical Research },
year = {2022},
volume = {38},
number = {1},
pages = {28--51},
abstract = {<p style="text-align: justify;">On the basis of a well-established binomial structure and the so-called Poisson-Lindley distribution, a new two-parameter discrete distribution
is introduced. Its properties are studied from both the theoretical and practical sides. For the theory, we discuss the moments, survival and hazard rate
functions, mode and quantile function. The statistical inference on the model
parameters is investigated by the maximum likelihood, moments, proportions,
least square, and weighted least square estimations. A simulation study is conducted to observe the performance of the bias and mean square error of the
obtained estimates. Then, applications to two practical data sets are given.
Finally, we construct a new flexible count data regression model called the
binomial-Poisson Lindley regression model with two practical examples in the
medical area.</p>},
issn = {2707-8523},
doi = {https://doi.org/10.4208/cmr.2021-0045},
url = {https://global-sci.com/article/81474/the-binomial-discrete-poisson-lindley-model-modeling-and-applications-to-count-regression}
}