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We describe a formal approach based on graphical causal models to identify the "root causes" of the change in the probability distribution of variables. After factorizing the joint distribution into conditional distributions of each…

Methodology · Statistics 2021-05-25 Kailash Budhathoki , Dominik Janzing , Patrick Bloebaum , Hoiyi Ng

When comparing two independent groups, shift functions are basically techniques that compare multiple quantiles rather than a single measure of location, the goal being to get a more detailed understanding of how the distributions differ.…

Methodology · Statistics 2023-12-11 Rand R. Wilcox , Guillaume A. Rousselet

The statistical duality of distributions is a powerful tool for statistical inferences. In the paper the statistical duality of Laplace distribution is discussed. As shown the confidence density of the parameter of this distribution is…

Statistics Theory · Mathematics 2007-06-13 E. A. Barkova , S. I. Bityukov , V. A. Taperechkina

The increasing availability of curated citation data provides a wealth of resources for analyzing and understanding the intellectual influence of scientific publications. In the field of statistics, current studies of citation data have…

Digital Libraries · Computer Science 2021-10-19 Lijia Wang , Xin Tong , Y. X. Rachel Wang

The accounts of medical trials provide very detailed information about the patients' health conditions. In contrast, only minimal data are usually given about demographic factors. Yet, some of these factors can have a notable impact on the…

Applications · Statistics 2015-06-16 Bertrand M. Roehner

The prior distribution on parameters of a sampling distribution is the usual starting point for Bayesian uncertainty quantification. In this paper, we present a different perspective which focuses on missing observations as the source of…

Methodology · Statistics 2021-11-23 Edwin Fong , Chris Holmes , Stephen G. Walker

Elections involving a very large voter population often lead to outcomes that surprise many. This is particularly important for the elections in which results affect the economy of a sizable population. A better prediction of the true…

Computer Science and Game Theory · Computer Science 2018-01-31 Palash Dey , Pravesh K. Kothari , Swaprava Nath

The chronic widespread misuse of statistics is usually inadvertent, not intentional. We find cautionary examples in a series of recent papers by Christakis and Fowler that advance statistical arguments for the transmission via social…

Methodology · Statistics 2011-07-05 Russell Lyons

Using methods of statistical mechanics, we analyse the effect of outliers on the supervised learning of a classification problem. The learning strategy aims at selecting informative examples and discarding outliers. We compare two…

Disordered Systems and Neural Networks · Physics 2009-10-31 Rainer Dietrich , Manfred Opper

Study of charged particle multiplicity distribution in high energy interactions of particles helps in revealing the dynamics of particle production and the underlying statistical patterns, which these distributions follow. Several…

High Energy Physics - Phenomenology · Physics 2020-01-30 R. Aggarwal , M. Kaur

A mutation will affect an individual and some or all of its descendants. In this paper, we investigate ordered trees with a distinguished vertex called the mutator. We describe various mutations in ordered trees, and find the generating…

Combinatorics · Mathematics 2014-10-07 Gi-Sang Cheon , Hana Kim , Louis W. Shapiro

In his 1986 book, Aitchison explains that compositional data is regularly mishandled in statistical analyses, a pattern that continues to this day. The Dirichlet Type I distribution is a multivariate distribution commonly used to model a…

Statistics Theory · Mathematics 2018-04-06 Sean van der Merwe , Daan de Waal

This study aims to understand how statistical biases affect the model's ability to generalize to in-distribution and out-of-distribution data on algorithmic tasks. Prior research indicates that transformers may inadvertently learn to rely…

Machine Learning · Computer Science 2024-09-11 John Mitros

Recent advances on human dynamics have focused on the normal patterns of human activities, with the quantitative understanding of human behavior under extreme events remaining a crucial missing chapter. This has a wide array of potential…

Physics and Society · Physics 2014-06-27 Liang Gao , Chaoming Song , Ziyou Gao , Albert-László Barabási , James P. Bagrow , Dashun Wang

The occurrence of the nonzero leftmost digit, i.e., 1, 2, ..., 9, of numbers from many real world sources is not uniformly distributed as one might naively expect, but instead, the nature favors smaller ones according to a logarithmic…

Data Analysis, Statistics and Probability · Physics 2014-11-21 Lijing Shao , Bo-Qiang Ma

In many real-world prediction tasks, class labels contain information about the relative order between labels that are not captured by commonly used loss functions such as multicategory cross-entropy. Recently, the preference for unimodal…

Machine Learning · Computer Science 2025-03-21 Jaime S. Cardoso , Ricardo Cruz , Tomé Albuquerque

In the United States, firearm-related deaths and injuries are a major public health issue. Because of limited federal action, state policies are particularly important, and their evaluation informs the actions of other policymakers. The…

Applications · Statistics 2025-12-17 Lee Kennedy-Shaffer , Alan Hamilton Kennedy

Opinion dynamics have fascinated researchers for centuries. The ability of societies to learn as well as the emergence of irrational {\it herding} are equally evident. The simplest example is that of agents that have to determine a binary…

Social and Information Networks · Computer Science 2017-04-07 Amir Leshem , Anna Scaglione

We study the problem of predicting numeric labels that are constrained to the integers or to a subrange of the integers. For example, the number of up-votes on social media posts, or the number of bicycles available at a public rental…

Machine Learning · Computer Science 2026-04-14 Bas Maat , Peter Bloem

The sudden appearance of modern machine learning (ML) phenomena like double descent and benign overfitting may leave many classically trained statisticians feeling uneasy -- these phenomena appear to go against the very core of statistical…

Machine Learning · Statistics 2024-09-30 Alicia Curth
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