activity
20082023
most citedMajorization: Here, There and Everywhere

50 citations · 66 across the 7 of their papers we have counts for

collaborators

7 papers

math.ST2023

Some power function distribution processes

Barry C. Arnold, Sachin Sachdeva, B. G. Manjunath

It is known that all the proportional reversed hazard (PRH) processes can be de?rived by a marginal transformation applied to a power function distribution (PFD) process. Kundu [8]…

stat.ME2023

On classical and Bayesian inference for bivariate Poisson conditionals distributions: Theory, methods and applications

Barry C. Arnold, Indranil Ghosh

Bivariate count data arise in several different disciplines (epidemiology, marketing, sports statistics, etc., to name but a few) and the bivariate Poisson distribution which is a…

math.ST2022

Bivariate distributions with equi-dispersed normal conditionals and related models

Barry C. Arnold, B. G. Manjunath

A random variable is equi-dispersed if its mean equals its variance. A Poisson distribution is a classical example of this phenomenon. However, a less well-known fact is that the c…

stat.ME2020★ 2 cited

Statistical Inference for distributions with one Poisson conditional

Barry C. Arnold, B. G. Manjunath

It will be recalled that the classical bivariate normal distributions have normal marginals and normal conditionals. It is natural to ask whether a similar phenomenon can be encoun…

stat.ME2017★ 5 cited

Adversarial and Amiable Inference in Medical Diagnosis, Reliability, and Survival Analysis

Nozer D. Singpurwalla, Barry C. Arnold, Joseph L. Gastwirth +2

In this paper, we develop a family of bivariate beta distributions that encapsulate both positive and negative correlations, and which can be of general interest for Bayesian infer…

math.ST2008★ 9 cited

Distributions that are both log-symmetric and R-symmetric

M. C. Jones, Barry C. Arnold

Two concepts of symmetry for the distributions of positive random variables are log-symmetry (symmetry of the distribution of ) and R-symmetry [7]. In this paper, we ch…