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There are over 55 different ways to construct a confidence respectively credible interval (CI) for the binomial proportion. Methods to compare them are necessary to decide which should be used in practice. The interval score has been…

Methodology · Statistics 2022-07-08 Lisa J. Hofer , Leonhard Held

The Maximal Information Coefficient (MIC) of Reshef et al. (Science, 2011) is a statistic for measuring dependence between variable pairs in large datasets. In this note, we prove that MIC is a consistent estimator of the corresponding…

Methodology · Statistics 2021-07-09 John Lazarsfeld , Aaron Johnson

We study competitive equilibrium in the canonical Fisher market model, but with indivisible goods. In this model, every agent has a budget of artificial currency with which to purchase bundles of goods. Equilibrium prices match between…

Computer Science and Game Theory · Computer Science 2019-11-25 Moshe Babaioff , Noam Nisan , Inbal Talgam-Cohen

We study the problem of computing a competitive equilibrium with approximately optimal bundles in Fisher markets with separable piecewise-linear concave (SPLC) utility functions, meaning that every buyer receives a $(1-\delta)$-optimal…

Computer Science and Game Theory · Computer Science 2026-05-01 Argyrios Deligkas , John Fearnley , Alexandros Hollender , Themistoklis Melissourgos

This paper uses new and recently introduced mathematical techniques to undertake a data-driven study on the systemic nature of global inflation. We start by investigating country CPI inflation over the past 70 years. There, we highlight the…

Mathematical Finance · Quantitative Finance 2022-03-02 Nick James , Kevin Chin

The aim of the present paper is to provide criteria for a central bank of how to choose among different monetary-policy rules when caring about a number of policy targets such as the output gap and expected inflation. Special attention is…

General Economics · Economics 2020-12-08 Jean-Bernard Chatelain , Kirsten Ralf

The Fisher information matrix can be used to characterize the local geometry of the parameter space of neural networks. It elucidates insightful theories and useful tools to understand and optimize neural networks. Given its high…

Machine Learning · Computer Science 2024-10-31 Alexander Soen , Ke Sun

Counterfactual explanations (CEs) provide an intuitive way to understand recommender systems by identifying minimal modifications to user-item interactions that alter recommendation outcomes. Existing CE methods for recommender systems,…

The Theil index is much used in economy and finance; it looks like the Shannon entropy, but pertains to event values rather than to their probabilities. Any time series can be remapped through the Theil index. Correlation coefficients can…

Data Analysis, Statistics and Probability · Physics 2012-09-04 Marcel Ausloos , Janusz Miskiewicz

We initiate the study of statistical inference and A/B testing for two market equilibrium models: linear Fisher market (LFM) equilibrium and first-price pacing equilibrium (FPPE). LFM arises from fair resource allocation systems such as…

Computer Science and Game Theory · Computer Science 2025-03-10 Luofeng Liao , Christian Kroer

The linear Fisher market (LFM) is a basic equilibrium model from economics, which also has applications in fair and efficient resource allocation. First-price pacing equilibrium (FPPE) is a model capturing budget-management mechanisms in…

Statistics Theory · Mathematics 2025-03-11 Luofeng Liao , Christian Kroer

The global financial system is highly complex, with cross-border interconnections and interdependencies. In this highly interconnected environment, local financial shocks and events can be easily amplified and turned into global events.…

Statistical Finance · Quantitative Finance 2021-04-22 Matthias Raddant , Dror Y. Kenett

Monthly and weekly economic indicators are often taken to be the largest common factor estimated from high and low frequency data, either separately or jointly. To incorporate mixed frequency information without directly modeling them, we…

Econometrics · Economics 2023-10-10 Serena Ng , Susannah Scanlan

The planning and design of future experiments rely heavily on forecasting to assess the potential scientific value provided by a hypothetical set of measurements. The Fisher information matrix, due to its convenient properties and low…

Cosmology and Nongalactic Astrophysics · Physics 2023-05-10 Joseph Ryan , Brandon Stevenson , Cynthia Trendafilova , Joel Meyers

We propose confidence regions with asymptotically correct uniform coverage probability of parameters whose Fisher information matrix can be singular at important points of the parameter set. Our work is motivated by the need for reliable…

Statistics Theory · Mathematics 2022-09-13 Karl Oskar Ekvall , Matteo Bottai

The Fisher information matrix is a quantity of fundamental importance for information geometry and asymptotic statistics. In practice, it is widely used to quickly estimate the expected information available in a data set and guide…

Methodology · Statistics 2023-06-06 William R. Coulton , Benjamin D. Wandelt

Valid and reliable measurement instruments are crucial for human factors in privacy research. We expect them to measure what they purport to measure, yielding validity, and to measure this consistently, offering us reliability. While there…

Human-Computer Interaction · Computer Science 2023-08-17 Thomas Groß

Automated story generation remains a difficult area of research because it lacks strong objective measures. Generated stories may be linguistically sound, but in many cases suffer poor narrative coherence required for a compelling,…

Computation and Language · Computer Science 2021-10-27 Louis Castricato , Spencer Frazier , Jonathan Balloch , Mark Riedl

Market equilibria of matching markets offer an intuitive and fair solution for matching problems without money with agents who have preferences over the items. Such a matching market can be viewed as a variation of Fisher market, albeit…

Computer Science and Game Theory · Computer Science 2017-04-03 Saeed Alaei , Pooya Jalaly , Eva Tardos

Generalization error predictors (GEPs) aim to predict model performance on unseen distributions by deriving dataset-level error estimates from sample-level scores. However, GEPs often utilize disparate mechanisms (e.g., regressors,…

Machine Learning · Computer Science 2023-05-30 Puja Trivedi , Danai Koutra , Jayaraman J. Thiagarajan