From the 1 of 5 linked papers with an AI index.
5 papers
High-dimensional Sobolev tests on hyperspheres
Bruno Ebner, Eduardo GarcÃa-Portugués, Thomas Verdebout
The paper studies Sobolev tests for uniformity on high‑dimensional hyperspheres, deriving their asymptotic null distribution, consistency, and power against von Mises‑Fisher altern…
On Stein's test of uniformity on the hypersphere
Paul Axmann, Bruno Ebner, Eduardo GarcÃa-Portugués
We propose a new test of uniformity on the hypersphere based on a Stein characterization associated with the Laplace-Beltrami operator. We identify a sufficient class of test funct…
A Stein Characterization-type Omnibus Tests for the Discrete Pareto Distribution
Deepesh Bhati, Bruno Ebner, Sakshi Khandelwal
The discrete Pareto (or Zeta, Zipf) distribution, arises naturally in modeling rank-frequency data across diverse fields such as linguistics, demography, biology, and computer scie…
A goodness-of-fit test for the Zeta distribution with unknown parameter
Bruno Ebner, Daniel Hlubinka
We introduce a new goodness-of-fit test for count data on for the Zeta distribution with unknown parameter. The test is built on a Stein-type characterization that use…
Stein's Method of Moments
Bruno Ebner, Adrian Fischer, Robert E. Gaunt +2
Stein operators allow to characterise probability distributions via differential operators. Based on these characterisations, we develop a new method of point estimation for margin…