Articles by YoungStatS

Algorithmic Fairness

September 18, 2023 | YoungStatS

Algorithmic Fairness Tuesday, October 3rd, 2023, 7:30 PT / 10:30 ET / 15:30 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...
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Testing multiple differences via symmetric hierarchical Dirichlet processes

August 16, 2023 | YoungStatS

Testing differences: from ANOVA to BNP Detecting and quantifying differences between groups is a problem of crucial significance across various fields, often addressed by practitioners using standard analysis of variance (ANOVA). However, ANOVA is subject to several well-known limitations. It primarily detects differences only in group means, assumes homogeneity within ...
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Illustration of Graphical Gaussian Process models to analyze highly multivariate spatial data

July 6, 2023 | YoungStatS

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, ...
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The scaling limit of Baxter permutations

July 1, 2023 | YoungStatS

Meanders, monotone meanders, and Baxter permutations 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 ...
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Recent advances in extreme value theory

April 3, 2023 | YoungStatS

Recent advances in extreme value theory Thursday, April 20th, 6:00 PT / 9:00 ET / 15:00 CET Extreme value theory is concerned with the accurate statistical assessment of the risk of rare events. Such extreme events have small occurrence probabiliti...
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Asymptotic Statistics in Non-Sparse Networks

February 25, 2023 | YoungStatS

Exchangeable arrays have been studied since the late 70’s (Aldous (1983), Kallenberg (2005)). Eagleson and Weber (1978) and Silverman (1976) establish Strong Law of Large Numbers and Central Limit Theorems for such arrays. Because non-sparse networks and multiway clustering are related to exchangeable arrays, they have received recent attention in statistics and econometrics (Davezies, ...
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Merry Christmas and Happy New Year 2023!

December 20, 2022 | YoungStatS

Dear Followers of the YoungStatS project, Dear All! It has been an exciting year for our project, including 7 One World YoungStatS webinars and blogposts from leading authors in different areas of statistics, probability and econometrics. In partic...
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Inference on Adaptively Collected Data

October 10, 2022 | YoungStatS

Abstract It is increasingly common for data to be collected adaptively, where experimental costs are reduced progressively by assigning promising treatments more frequently. However, adaptivity also poses great challenges on post-experiment inferen...
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Inference on Adaptively Collected Data

October 10, 2022 | YoungStatS

Abstract It is increasingly common for data to be collected adaptively, where experimental costs are reduced progressively by assigning promising treatments more frequently. However, adaptivity also poses great challenges on post-experiment inferen...
[Read more...]
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