Extrapolation to unseen domains: from theory to applications Monday, April 22nd, 2024, 8:00 PT / 11:00 ET / 17:00 CET 3rd joint webinar of the IMS New Researchers Group, Young Data Science Researcher Seminar Zürich and the YoungStatS Project. When ... [Read more...]

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Introduction The Lévy distribution, together with the Normal and Cauchy distribution, belongs to the class of stable distributions, and it is among the only three distributions for which the density can be derived in a closed form. The density func... [Read more...]

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Dear Followers of the YoungStatS project, Dear All! It has been another intense year for our project, including 4 novel One World YoungStatS webinars, 12 blogposts from leading authors in various areas of statistics and data science, probability an... [Read more...]

Background Circular data, i.e., data defined on the unit circle, can be found in many areas of science. The unique nature of these data means that conventional methods for non-circular data are not valid for these. At the same time, advances in geographical information and global positioning systems have ... [Read more...]

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Overview Sets of graphs arise in many different applications, from medicine to finance, from urban planning to social science. Analysing sets of graphs is far from trivial as they are strongly non Euclidean data type. There are two main sets of gra... [Read more...]

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Stochastic Fluid Dynamics Wednesday, November 15th, 6:00 PT / 9:00 ET / 15:00 CET The study of fluid dynamics equations with white forcing is a classical topic in SPDEs and ergodic theory. Recently a new wave of interest, with a shift in focus towa... [Read more...]

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Overview In this post we present a new estimation procedure for functional linear regression useful when the regression surface – or curve – is supposed to be exactly zero within specific regions of its domain. Our approach involves regularization ... [Read more...]

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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. Crossed random effects models (CREM) CREM model a continuous response variables \(Y\) as depending on ... [Read more...]

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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: Tuesday, October 3rd, 20... [Read more...]

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Introduction 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 locations for each variable and those among the variables. In this document, ... [Read more...]