2 citations · 4 across the 7 of their papers we have counts for
7 papers
Beyond Pairwise: Nonparametric Kernel Estimators for a Generalized Weitzman Coefficient Across k Distributions
Omar Eidous, Noura Almasri
This papers presents a generalization of the Weitzman overlapping coefficient, originally defined for two probability density functions, to a setting involving k independent distri…
A Simpson Based Estimation Approach for the Overlapping Coefficient of k>=2 Normal Distributions
Omar Eidous, Majd Alsheyyab
The overlapping coefficient is a fundamental measure of similarity between probability distributions. While the case of two distributions has been extensively studied, extending th…
Enhancing Wildlife Density Estimation: A New Two-Parameter Detection Function for Line Transect Sampling
Midhat M. Edous, Omar M. Eidous
Accurate estimation of wildlife density is vital for effective ecological monitoring, conservation, and management. Line transect sampling, a central technique in distance sampling…
On Inference of Weitzman Overlapping Coefficient in Two Weibull Distributions
Omar Eidous, Hala Maqableh
Studying overlapping coefficients has recently become of great benefit, especially after its use in goodness-of-fit tests. These coefficients are defined as the amount of similarit…
Approximations for Standard Normal Distribution Function and Its Invertible
Omar M. Eidous, Mohammad Al-Rawash
In this paper, we introduce a new approximation of the cumulative distribution function of the standard normal distribution based on Tocher's approximation. Also, we assess the qua…
Estimation of Matusita Overlapping Coefficient for Pair Normal Distributions
Omar Eidous, Salam Al-Daradkeh
The Matusita overlapping coefficient is defined as agreement or similarity between two or more distributions. The parametric normal distribution is one of the most important statis…
Improvements of Polya Upper Bound for Cumulative Standard Normal Distribution and Related Functions
Omar Eidous
Although there is an extensive literature on the upper bound for cumulative standard normal distribution, there are relatively not sharp for all values of the interested argument x…