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The COVID-19 pandemic has plagued the world for months. The U.S. has taken measures to counter it. On a daily basis, newly confirmed cases have been reported. In the early days, these numbers showed an increasing trend. Recently, the…

Physics and Society · Physics 2020-05-21 Xiubin Bruce Wang , Chaolun Ma

We consider a compressed sensing problem in which both the measurement and the sparsifying systems are assumed to be frames (not necessarily tight) of the underlying Hilbert space of signals, which may be finite or infinite dimensional. The…

Information Theory · Computer Science 2020-10-15 Giovanni S. Alberti , Matteo Santacesaria

There has been an increasing interest in press freedom in the face of various global scandals, transformation of media, technological change, obstacles to deliberative democracy, and other factors. Press freedom is frequently used also as…

Computers and Society · Computer Science 2023-09-20 Jukka Ruohonen

The problem of consensus in the presence of adversarially behaving agents has been studied extensively in the literature. The proposed algorithms typically guarantee that the consensus value lies within the convex hull of initial normal…

Systems and Control · Electrical Eng. & Systems 2019-06-20 James Usevitch , Dimitra Panagou

Ordered response scales are ubiquitous in economics, but their interpretation rests on an untested assumption: that numerical labels reflect equal psychological intervals. The contribution of this paper is to provide a systematic assessment…

General Economics · Economics 2025-09-03 Caspar Kaiser , Anthony Lepinteur

We propose an approach to estimate the effect of multiple simultaneous interventions in the presence of hidden confounders. To overcome the problem of hidden confounding, we consider the setting where we have access to not only the…

Methodology · Statistics 2020-06-17 Sorawit Saengkyongam , Ricardo Silva

A common assumption in causal inference from observational data is that there is no hidden confounding. Yet it is, in general, impossible to verify this assumption from a single dataset. Under the assumption of independent causal mechanisms…

Methodology · Statistics 2023-11-07 Rickard K. A. Karlsson , Jesse H. Krijthe

Segmented regression is a standard statistical procedure used to estimate the effect of a policy intervention on time series outcomes. This statistical method assumes the normality of the outcome variable, a large sample size, no…

Applications · Statistics 2020-02-18 Mohammad M. Islam , Ph. D. , Erik L. Heiny , Ph. D

Epidemic models often reflect characteristic features of infectious spreading processes by coupled non-linear differential equations considering different states of health (such as Susceptible, Infected, or Recovered). This compartmental…

Physics and Society · Physics 2021-12-01 Vaiva Vasiliauskaite , Nino Antulov-Fantulin , Dirk Helbing

To deploy machine learning models on-device, practitioners use compression algorithms to shrink and speed up models while maintaining their high-quality output. A critical aspect of compression in practice is model comparison, including…

Human-Computer Interaction · Computer Science 2025-01-27 Angie Boggust , Venkatesh Sivaraman , Yannick Assogba , Donghao Ren , Dominik Moritz , Fred Hohman

We introduce and analyze several variants of a system of differential equations which model the dynamics of social outbursts, such as riots. The systems involve the coupling of an explicit variable representing the intensity of rioting…

Analysis of PDEs · Mathematics 2015-07-08 Henri Berestycki , Jean-Pierre Nadal , Nancy Rodriguez

In contemporary society, the escalating pressures of life and work have propelled psychological disorders to the forefront of modern health concerns, an issue that has been further accentuated by the COVID-19 pandemic. The prevalence of…

Machine Learning · Computer Science 2024-01-09 Qiang Li , Yufeng Wu , Zhan Xu , Hefeng Zhou

Unobserved confounding is one of the main challenges when estimating causal effects. We propose a causal reduction method that, given a causal model, replaces an arbitrary number of possibly high-dimensional latent confounders with a single…

Machine Learning · Statistics 2023-02-24 Maximilian Ilse , Patrick Forré , Max Welling , Joris M. Mooij

Microscopic models describing a whole of economic interactions in a closed society are considered. The presence of a tax system combined with a redistribution process is taken into account, as well as the occurrence of tax evasion. In…

General Finance · Quantitative Finance 2017-01-11 M. L. Bertotti , G. Modanese

Decomposing an exposure effect on an outcome into separate natural indirect effects through multiple mediators requires strict assumptions, such as correctly postulating the causal structure of the mediators, and no unmeasured confounding…

Methodology · Statistics 2021-02-04 Wen Wei Loh , Beatrijs Moerkerke , Tom Loeys , Stijn Vansteelandt

We consider the problem of sequential detection of a change in the statistical behavior of a hidden Markov model. By adopting a worst-case analysis with respect to the time of change and by taking into account the data that can be accessed…

Statistics Theory · Mathematics 2019-01-29 George V. Moustakides

Whereas confidence intervals are used to assess uncertainty due to unmeasured individuals, confounding intervals can be used to assess uncertainty due to unmeasured attributes. Previously, we have introduced a methodology for computing…

Methodology · Statistics 2025-08-13 Brian Knaeble , R Mitchell Hughes

We introduce a new opinion dynamics model where a group of agents holds two kinds of opinions: inherent and declared. Each agent's inherent opinion is fixed and unobservable by the other agents. At each time step, agents broadcast their…

Systems and Control · Electrical Eng. & Systems 2022-05-04 Ali Jadbabaie , Anuran Makur , Elchanan Mossel , Rabih Salhab

We hypothesize that if election results are manipulated or forged, then, due to the well-known human attraction to round numbers, the frequency of reported round percentages can be increased. To test this hypothesis, we analyzed raw data…

Applications · Statistics 2016-06-30 Dmitry Kobak , Sergey Shpilkin , Maxim S. Pshenichnikov

We study combinations of risk measures under no restrictive assumption on the set of alternatives. We develop and discuss results regarding the preservation of properties and acceptance sets for the combinations of risk measures. One of the…

Mathematical Finance · Quantitative Finance 2023-05-09 Marcelo Brutti Righi