YoungStatS
The blog of Young Statisticians Europe (YSE)
bayesian-statistics
Linear-cost unbiased estimator for large crossed random effect models via couplings
Paolo Ceriani and Giacomo Zanella
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2023-09-27
In the following we show how it is possible to obtain parallelizable, unbiased and computationally cheap estimates of Crossed random effects models with a linear cost in the number of datapoints (and paramaters) exploiting couplings. […] CREM model a continuous response variables \(Y\) as…
webinars
Algorithmic Fairness
2023-09-19
Algorithmic Fairness Tuesday, October 3rd, 2023, 7:30 PT / 10:30 ET / 16:30 CET 2nd joint webinar of the IMS New Researchers Group, Young Data Science Researcher Seminar Zürich and the YoungStatS Project. When & Where: […] Speakers: […] Abstract: Multi-calibration is a powerful and…
graphical-models
Illustration of Graphical Gaussian Process models to analyze highly multivariate spatial data
Debangan Dey, Abhirup Datta, Sudipto Banerjee
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2023-07-07
Abundant multivariate spatial data from the natural and environmental sciences demands research on the joint distribution of multiple spatially dependent variables (Wackernagel (2013), Cressie and Wikle (2011), Banerjee and Gelfand (2014)). Here, our goal is to estimate associations over spatial…
random-geometry
The scaling limit of Baxter permutations
Jacopo Borga
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2023-07-02
Versions of the following question can be traced back at least to the work of Henri Poincaré (Poincaré (1912)): In how many ways a simple loop in the plane can cross a line a specified number of times? Despite many efforts, this question remains open after more than a century. Let us start by…
bayesian-nonparametrics
Bayesian nonparametric modeling of conditional multidimensional dependence structures
Rosario Barone and Luciana Dalla Valle
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2023-05-19
In many real data applications we are often required to model jointly \(d\geq 3\) continuous random variables, denoted as \(Y_1,\dots,Y_d\) . The multivariate distribution, which allows us to describe the joint behaviour of those variables, can be denoted as \(F(Y_1,\dots,Y_d)=P(Y_1\le…
stochastic-differential-equations
Chaotic mixing and the statistical properties of scalar turbulence
Sam Punshon-Smith
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2023-04-10
Passive scalar turbulence is the study of how a scalar quantity, such as temperature or salinity, is transported by an incompressible fluid. This process is modeled by the advection diffusion equation \[\begin{equation} \partial_tg_t + u_t\cdot\nabla g_t - \kappa \Delta g_t =…
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