3 citations · 3 across the 2 of their papers we have counts for
3 papers
stat.AP2023
Clustering MIC data through Bayesian mixture models: an application to detect M. Tuberculosis resistance mutations
Clara Grazian
Antimicrobial resistance is becoming a major threat to public health throughout the world. Researchers are attempting to contrast it by developing both new antibiotics and patient-…
stat.ME2023★ 3 cited
Advances in Bayesian random partition models: A comprehensive review
Clara Grazian
Clustering is a crucial task in various domains of knowledge, including medicine, epidemiology, genomics, environmental science, economics, and visual sciences, among others. Metho…
stat.ME2018
On a Loss-based prior for the number of components in mixture models
Clara Grazian, Cristiano Villa, Brunero Liseo
We propose a prior distribution for the number of components of a finite mixture model. The novelty is that the prior distribution is obtained by considering the loss one would inc…