Exploring the Potential of the Kumaraswamy Discrete Half-Logistic Distribution in Data Science Scanning and Decision-Making
Data science often employs discrete probability distributions to model and analyze various
phenomena. These distributions are particularly useful when dealing with data that can be …
phenomena. These distributions are particularly useful when dealing with data that can be …
A new discrete distribution on integers: Analytical and applied study on stock exchange and flood data
This paper is devoted to the properties and applications of a new one-parameter discrete
distribution with support on integers. The new distribution represents a discrete analogue of …
distribution with support on integers. The new distribution represents a discrete analogue of …
The Poisson-Lindley difference model with application to discrete stock price change
This paper is devoted to the properties and applications of a new discrete model on Z. This
model represents the difference of two independent Poisson-Lindley random variables with …
model represents the difference of two independent Poisson-Lindley random variables with …
Software test-run reliability modeling with non-homogeneous binomial processes
While the number of test runs (test cases) is often used to define the time scale to measure
quantitative software reliability, the common calendar-time modeling with non …
quantitative software reliability, the common calendar-time modeling with non …
Regression models for double discrete distributions
AS Alzaidani, EEAA Aly - Bulletin of the Malaysian Mathematical Sciences …, 2022 - Springer
We propose and study a number of regression models for discrete distributions taking
values in the set Z= 0,±1,±2,⋯. These models are based on extensions of the random sign …
values in the set Z= 0,±1,±2,⋯. These models are based on extensions of the random sign …