Zobrazeno 1 - 10
of 111
pro vyhledávání: '"Julyan Arbel"'
This book includes the lectures given during the third session of the School of Statistics for Astrophysics that took place at Autrans, near Grenoble, in France, in October 2017. The subject is Bayesian Methodology.The interest of this statistical ap
Publikováno v:
HGG Advances, Vol 3, Iss 4, Pp 100136- (2022)
Summary: Publicly available genome-wide association studies (GWAS) summary statistics exhibit uneven quality, which can impact the validity of follow-up analyses. First, we present an overview of possible misspecifications that come with GWAS summary
Externí odkaz:
https://doaj.org/article/422e9b5d08034812845b0a504ffe9136
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
Publikováno v:
IEEE Access, Vol 8, Pp 131683-131698 (2020)
Approximate Bayesian computation (ABC) has become an essential part of the Bayesian toolbox for addressing problems in which the likelihood is prohibitively expensive or entirely unknown, making it intractable. ABC defines a pseudo-posterior by compa
Externí odkaz:
https://doaj.org/article/371f7d125ba54e3da48cbda621d1e730
Autor:
Daria Bystrova, Giovanni Poggiato, Billur Bektaş, Julyan Arbel, James S. Clark, Alessandra Guglielmi, Wilfried Thuiller
Publikováno v:
Frontiers in Ecology and Evolution, Vol 9 (2021)
Modeling species distributions over space and time is one of the major research topics in both ecology and conservation biology. Joint Species Distribution models (JSDMs) have recently been introduced as a tool to better model community data, by infe
Externí odkaz:
https://doaj.org/article/f9a95abc40ba44e4803e96e7a9e8ab08
Publikováno v:
Journal of Statistical Planning and Inference
Journal of Statistical Planning and Inference, 2023, 225, pp.146-170. ⟨10.1016/j.jspi.2022.12.001⟩
Journal of Statistical Planning and Inference, 2023, 225, pp.146-170. ⟨10.1016/j.jspi.2022.12.001⟩
International audience; Expectiles form a family of risk measures that have recently gained interest over the more common value-at-risk or return levels, primarily due to their capability to be determined by the probabilities of tail values and magni
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aff56b9c74d8026868b04de7f22ecc5e
https://inria.hal.science/hal-03428827v2/file/main.pdf
https://inria.hal.science/hal-03428827v2/file/main.pdf
Autor:
Minh Tri Lê, Julyan Arbel
Publikováno v:
Proceedings of the 3rd Workshop on Machine Learning and Systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5aa548b347f1d24be34b4b164e98e74
https://doi.org/10.1145/3578356.3592586
https://doi.org/10.1145/3578356.3592586
Publikováno v:
Australian and New Zealand Journal of Statistics
Australian and New Zealand Journal of Statistics, 2021, 63 (3), pp.542-564. ⟨10.1111/anzs.12342⟩
Australian and New Zealand Journal of Statistics, 2021, 63 (3), pp.542-564. ⟨10.1111/anzs.12342⟩
International audience; Robust statistical data modelling under potential model mis-specification often requires leaving the parametric world for the nonparametric. In the latter, parameters are infinite dimensional objects such as functions, probabi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f66855576038c9ca0330b5832ace9ad8
https://doi.org/10.1111/anzs.12342
https://doi.org/10.1111/anzs.12342
Publikováno v:
Statistics and Computing. 32
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ec0869c1743ecd59d13936777b16db2
https://doi.org/10.1007/s11222-022-10155-6
https://doi.org/10.1007/s11222-022-10155-6
Publikováno v:
Approches statistiques pour les variables cachées en écologie ISBN: 9781789480474
Nous présentons les modèles à facteurs latents dans le contexte des modèles de distribution joints d'espèces (JSDM), en soulignant leur utilité en écologie des communautés. Ces modèles permettent de faire face à la grande dimension des donn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e8329e02188c86c9ad5b55cba920ac6b
https://doi.org/10.51926/iste.9047.ch7
https://doi.org/10.51926/iste.9047.ch7