On the Hurwitz zeta function with an application to the beta-exponential distribution

Autor: Julyan Arbel, Olivier Marchal, Bernardo Nipoti

Publikováno v: Journal of Inequalities and Applications, Vol 2020, Iss 1, Pp 1-8 (2020)

Abstract We prove a monotonicity property of the Hurwitz zeta function which, in turn, translates into a chain of inequalities for polygamma functions of different orders. We provide a probabilistic interpretation of our result by exploiting a connec

Externí odkaz: https://doaj.org/article/a59f743d6f8e4380a788f32959c10b5d

Nonparametric Bayesian modelling of longitudinally integrated covariance functions on spheres

Autor: Pier Giovanni Bissiri, Galatia Cleanthous, Xavier Emery, Bernardo Nipoti, Emilio Porcu

Taking into account axial symmetry in the covariance function of a Gaussian random field is essential when the purpose is modelling data defined over a large portion of the sphere representing our planet. Axially symmetric covariance functions admit

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f83be850774867191a3187157dff8d6
https://hdl.handle.net/10281/396631

Dirichlet process mixtures under affine transformations of the data

Autor: Riccardo Corradin, Julyan Arbel, Bernardo Nipoti

Publikováno v: Computational Statistics
Computational Statistics, Springer Verlag, 2021, 36, pp.577-601. ⟨10.1007/s00180-020-01013-y⟩
Computational Statistics, 2021, 36, pp.577-601. ⟨10.1007/s00180-020-01013-y⟩

Location-scale Dirichlet process mixtures of Gaussians (DPM-G) have proved extremely useful in dealing with density estimation and clustering problems in a wide range of domains. Motivated by an astronomical application, in this work we address the r

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8cdc920576c4af46ba463442803204fc
https://hal.archives-ouvertes.fr/hal-01950652

Optimal stratification of survival data via Bayesian nonparametric mixtures

Autor: Luis E. Nieto-Barajas, Riccardo Corradin, Bernardo Nipoti

The stratified proportional hazards model represents a simple solution to account for heterogeneity within the data while keeping the multiplicative effect on the hazard function. Strata are typically defined a priori by resorting to the values taken

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26fbb70e0a9c1664af3e307f65e1b2c6

A Bayesian semiparametric partially PH model for clustered time-to-event data

Autor: Bernardo Nipoti, Alejandro Jara, Michele Guindani

Publikováno v: Scandinavian Journal of Statistics. 45:1016-1035

A standard approach for dealing with unobserved heterogeneity and clustered time‐to‐event data within the proportional hazards (PH) context has been the introduction of a cluster‐specific random effect (frailty), common to subjects within the s

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bcf236cd552363f12745f033603b142f
https://doi.org/10.1111/sjos.12332