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Posterior Moments of the Cauchy Distribution

1999
The posterior moments of parameters specifying distributions are minimum mean square Bayesian estimators for the corresponding moments of those parameters, and as such are ubiquitous in the Bayesian approach to statistical inference of distributions. The Cauchy distribution is most notable for its wide tails, decided absence of high-order moments, and ...
openaire   +2 more sources

Locally optimum watermark decoder in NSST domain using RSS-based Cauchy distribution

Multimedia tools and applications, 2020
Pan-pan Niu   +4 more
semanticscholar   +1 more source

Half-Cauchy and Power Cauchy Distributions: Ordinary Differential Equations

2018
In this chapter, homogenous ordinary differential equations (ODES) of different orders were obtained for the probability density function, quantile function, survival function inverse survival function, hazard function and reversed hazard functions of half-Cauchy and power Cauchy distributions.
Ezinne C. Erondu   +4 more
openaire   +2 more sources

Cancer statistics for adolescents and young adults, 2020

Ca-A Cancer Journal for Clinicians, 2020
Kimberly D Miller   +2 more
exaly  

Data-Driven Robust RVFLNs Modeling of a Blast Furnace Iron-Making Process Using Cauchy Distribution Weighted M-Estimation

IEEE transactions on industrial electronics (1982. Print), 2017
P. Zhou, Youbin Lv, Hong Wang, T. Chai
semanticscholar   +1 more source

De-noising of ultrasound image using Bayesian approached heavy-tailed Cauchy distribution

Multimedia tools and applications, 2019
S. Sahu   +3 more
semanticscholar   +1 more source

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