Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Federico Camerlenghi"'
Autor:
Federico Camerlenghi, Stefano Favaro
Publikováno v:
Mathematics, Vol 9, Iss 22, p 2891 (2021)
In the 1920s, the English philosopher W.E. Johnson introduced a characterization of the symmetric Dirichlet prior distribution in terms of its predictive distribution. This is typically referred to as Johnson’s “sufficientness” postulate, and i
Externí odkaz:
https://doaj.org/article/afd2be041ecf41669e6c2c2c3cdce1ba
Publikováno v:
Image Analysis and Stereology, Vol 33, Iss 2, Pp 83-94 (2014)
Many real phenomena may be modelled as random closed sets in ℝd, of different Hausdorff dimensions. The problem of the estimation of pointwise mean densities of absolutely continuous, and spatially inhomogeneous, random sets with Hausdorff dimensio
Externí odkaz:
https://doaj.org/article/6d32769d08bd4a6185478a683a49780c
Publikováno v:
Journal of the American Statistical Association. :1-12
There is a growing interest in the estimation of the number of unseen features, mostly driven by biological applications. A recent work brought out a peculiar property of the popular completely random measures (CRMs) as prior models in Bayesian nonpa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47e0ddc8e8f8aa4d262d04bdc6e947b3
https://doi.org/10.1080/01621459.2022.2115918
https://doi.org/10.1080/01621459.2022.2115918
Partially exchangeable datasets are characterized by observations grouped into known, heterogeneous units. The recently developed Common Atoms Model (CAM) is a Bayesian nonparametric technique suited for analyzing this type of data. CAM induces a two
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1299::fedd3079d593d314f936ec41a09a7312
https://hdl.handle.net/10281/396460
https://hdl.handle.net/10281/396460
Gibbs-type priors are widely used as key components in several Bayesian nonparametric models. By virtue of their flexibility and mathematical tractability, they turn out to be predominant priors in species sampling problems, clustering and mixture mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25826c914d80c1b99f3a6a5cd54c36ef
http://arxiv.org/abs/2108.11997
http://arxiv.org/abs/2108.11997
Publikováno v:
The Annals of Statistics. 49
Hierarchical nonparametric processes are popular tools for defining priors on collections of probability distributions, which induce dependence across multiple samples. In survival analysis problems, one is typically interested in modeling the hazard
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::add0c4a20a8e133f767fd3a40d211443
https://doi.org/10.1214/20-aos1982
https://doi.org/10.1214/20-aos1982
The use of large datasets for targeted therapeutic interventions requires new ways to characterize the heterogeneity observed across subgroups of a specific population. In particular, models for partially exchangeable data are needed for inference on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1819292b72dd4073af1111831b620b11
Publikováno v:
Lancaster University-Pure
Consider an (observable) random sample of size n from an infinite population of individuals, each individual being endowed with a finite set of "features" from a collection of features (F-j)(j>1) with unknown probabilities (p(j))(j>1), i.e., p(j) is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::f3268fa558eccca49e4feb47bc283cac
http://hdl.handle.net/2318/1810646
http://hdl.handle.net/2318/1810646
Publikováno v:
Biometrika
While the cost of sequencing genomes has decreased dramatically in recent years, this expense often remains non-trivial. Under a fixed budget, then, scientists face a natural trade-off between quantity and quality; they can spend resources to sequenc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0dab1bda11d0b954519847dc69fe15e6
Protection against disclosure is a legal and ethical obligation for agencies releasing microdata files for public use. Consider a microdata sample of size $n$ from a finite population of size $\bar{n}=n+\lambda n$, with $\lambda>0$, such that each re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31a215d933163de5135cc229a0bfc4a0
http://hdl.handle.net/10281/280701
http://hdl.handle.net/10281/280701