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Turbulence theory is usually concerned with the statistical moments of the velocity or its fluctuations. One could also analyze the implicit probability distributions. This is the purview of information theory. Here we use information…

Chaotic Dynamics · Physics 2016-02-15 Rory T. Cerbus , Walter I. Goldburg

We revisit a model proposed by Freedman etal in \cite{freedman} which describes the dynamics of a population diffusing in a patchy environment. From their work it is known that positive steady states exist for this model, but not whether…

Dynamical Systems · Mathematics 2025-05-08 Patrick de Leenheer , Jane Shaw MacDonald , Swati Patel

We construct a general stochastic process and prove weak convergence results. It is scaled in space and through the parameters of its distribution. We show that our simplified scaling is equivalent to time scaling used frequently. The…

Probability · Mathematics 2011-07-01 Mine Caglar

Likelihood-based methods of statistical inference provide a useful general methodology that is appealing, as a straightforward asymptotic theory can be applied for their implementation. It is important to assess the relationships between…

Statistics Theory · Mathematics 2015-03-20 Thomas J. DiCiccio , Todd A. Kuffner , G. Alastair Young , Russell Zaretzki

Given two time series, can one tell, in a rigorous and quantitative way, the cause and effect between them? Based on a recently rigorized physical notion namely information flow, we arrive at a concise formula and give this challenging…

Methodology · Statistics 2014-03-27 X. San Liang

Power law or generalized polynomial regressions with unknown real-valued exponents and coefficients, and weakly dependent errors, are considered for observations over time, space or space--time. Consistency and asymptotic normality of…

Statistics Theory · Mathematics 2012-05-14 Peter M. Robinson

The Syrian civil war has been ongoing since 2011 and has already caused thousands of deaths. The analysis of death tolls helps to understand the dynamics of the conflict and to better allocate resources to the affected areas. In this…

Physics and Society · Physics 2021-02-09 Kazuki Fujita , Shigeru Shinomoto , Luis E C Rocha

This article presents a biological neural network model driven by inhomogeneous Poisson processes accounting for the intrinsic randomness of synapses. The main novelty is the introduction of local interactions: each firing neuron triggers…

Probability · Mathematics 2021-08-17 Maximiliano Altamirano , Roberto Cortez , Matthieu Jonckheere , Lasse Leskelä

Recent studies of human migration have focused on modern issues of international economics, politics, urbanization, or commuting. Here we make use of very large anonymized genealogies which offer quantitative metrics and models before…

Physics and Society · Physics 2024-10-25 Robin W. Spencer , Samuel M. Otterstrom

The study of associations and their causal explanations is a central research activity whose methodology varies tremendously across fields. Even within specialized subfields, comparisons across textbooks and journals reveals that the basics…

Methodology · Statistics 2025-10-13 Sander Greenland

The Poisson process is the most elementary continuous-time stochastic process that models a stream of repeating events. It is uniquely characterised by a single parameter called the rate. Instead of a single value for this rate, we here…

Probability · Mathematics 2019-06-05 Alexander Erreygers , Jasper De Bock

We study the connection between multi-fractality and crucial events. Multi-fractality is frequently used as a measure of physiological variability. Crucial events are known to play a fundamental role in the transport of information between…

Adaptation and Self-Organizing Systems · Physics 2018-01-03 Gyanendra Bohara , David Lambert , Bruce J. West , Paolo Grigolini

Previous models of international conflict have suffered two shortfalls. They tended not to embody dynamic changes, focusing rather on static slices of behavior over time. These models have also been empirically evaluated in ways that…

Applications · Statistics 2015-05-01 Shahryar Minhas , Peter D. Hoff , Michael D. Ward

A fundamental question in causal inference is whether it is possible to reliably infer manipulation effects from observational data. There are a variety of senses of asymptotic reliability in the statistical literature, among which the most…

Artificial Intelligence · Computer Science 2012-12-12 Jiji Zhang , Peter L. Spirtes

Intersectionality is a framework that analyzes how interlocking systems of power and oppression affect individuals along overlapping dimensions including race, gender, sexual orientation, class, and disability. Intersectionality theory…

Machine Learning · Computer Science 2019-09-11 James Foulds , Rashidul Islam , Kamrun Keya , Shimei Pan

We discuss recently developed methods that quantify the stability and generalizability of statistical findings under distributional changes. In many practical problems, the data is not drawn i.i.d. from the target population. For example,…

Methodology · Statistics 2023-10-05 Dominik Rothenhäusler , Peter Bühlmann

Information flow provides a natural measure for the causal interaction between dynamical events. This study extends our previous rigorous formalism of componentwise information flow to the bulk information flow between two complex…

Neurons and Cognition · Quantitative Biology 2021-12-30 X. San Liang

Separate modelling of cause specific mortality rates and their projections can yield inconsistent forecasts when the sum of deaths by cause does not match the total observed in a population. We develop a hierarchical probabilistic framework…

Applications · Statistics 2026-03-03 Andrea Nigri , Han Lin Shang , Francesco Ungolo

We first prove some general results on pathwise uniqueness, comparison property and existence of nonnegative strong solutions of stochastic equations driven by white noises and Poisson random measures. The results are then used to prove the…

Probability · Mathematics 2012-04-12 Donald A. Dawson , Zenghu Li

Philosophers now seem to agree that frequentism is an untenable strategy to explain the meaning of probabilities. Nevertheless, I want to revive frequentism, and I will do so by grounding probabilities on typicality in the same way as the…

History and Philosophy of Physics · Physics 2021-01-05 Mario Hubert
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