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We study weak convergence of empirical processes of dependent data $(X_i)_{i\geq0}$, indexed by classes of functions. Our results are especially suitable for data arising from dynamical systems and Markov chains, where the central limit…

Probability · Mathematics 2014-07-07 Herold Dehling , Olivier Durieu , Marco Tusche

We investigate continuous time random walks with truncated $\alpha$-stable trapping times. We prove distributional ergodicity for a class of observables; namely, the time-averaged observables follow the probability density function called…

Statistical Mechanics · Physics 2015-05-27 Tomoshige Miyaguchi , Takuma Akimoto

We consider the Bouchaud trap model on the integers in the case that the trap distribution has a slowly varying tail at infinity. Our main result is a functional limit theorem for the model under the annealed law, analogous to the…

Probability · Mathematics 2016-04-21 David Croydon , Stephen Muirhead

Disordered systems such as spin glasses have been used extensively as models for high-dimensional random landscapes and studied from the perspective of optimization algorithms. In a recent paper by L. Addario-Berry and the second author,…

Probability · Mathematics 2022-06-17 Fu-Hsuan Ho , Pascal Maillard

In this paper, we consider the discrete-time setting, and the market model described by (S,F,T)$. Herein F is the ``public" flow of information which is available to all agents overtime, S is the discounted price process of d-tradable…

Mathematical Finance · Quantitative Finance 2024-01-12 Tahir Choulli , Emmanuel Lepinette

In this paper, we consider the Gaussian process (GP) bandit optimization problem in a non-stationary environment. To capture external changes, the black-box function is allowed to be time-varying within a reproducing kernel Hilbert space…

Machine Learning · Computer Science 2022-03-29 Yuntian Deng , Xingyu Zhou , Baekjin Kim , Ambuj Tewari , Abhishek Gupta , Ness Shroff

Hidden Markov models are versatile tools for modeling sequential observations, where it is assumed that a hidden state process selects which of finitely many distributions generates any given observation. Specifically for time series of…

Methodology · Statistics 2019-01-11 Timo Adam , Roland Langrock , Christian H. Weiß

This paper develops a method for estimating housing production functions when builders choose capital after observing local conditions that are unobserved by the econometrician. Because observed capital variation reflects both technological…

General Economics · Economics 2026-05-06 Yusuke Adachi

This paper considers the problem of measuring the credit risk in portfolios of loans, bonds, and other instruments subject to possible default under multi-factor models. Due to the amount of the portfolio, the heterogeneous effect of…

Computational Finance · Quantitative Finance 2019-04-10 Cheng-Der Fuh , Chuan-Ju Wang

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

In this paper, we present a general derivation of a modified fluctuation-dissipation theorem (MFDT) valid near an arbitrary non-stationary state for a system obeying markovian dynamics. We show that the method to derive modified…

Statistical Mechanics · Physics 2011-12-23 Gatien Verley , Raphaël Chétrite , David Lacoste

An equation, strongly reminiscent of Fisher's equation, is used to model the response of tsetse populations to proposed control measures in the vicinity of a game reserve. The model assumes movement is by diffusion and that growth is…

Quantitative Methods · Quantitative Biology 2015-05-26 S. J. Childs

We consider a government that aims at reducing the debt-to-gross domestic product (GDP) ratio of a country. The government observes the level of the debt-to-GDP ratio and an indicator of the state of the economy, but does not directly…

Optimization and Control · Mathematics 2019-01-29 Giorgia Callegaro , Claudia Ceci , Giorgio Ferrari

In many scientific and engineering applications, we are tasked with the maximisation of an expensive to evaluate black box function $f$. Traditional settings for this problem assume just the availability of this single function. However, in…

Machine Learning · Statistics 2019-03-19 Kirthevasan Kandasamy , Gautam Dasarathy , Junier B. Oliva , Jeff Schneider , Barnabas Poczos

Survey data are widely used to study how income inequality, poverty, and welfare evolve over time. A common practice is to estimate the income distribution separately for each year, treating annual observations as independent…

Econometrics · Economics 2026-04-24 David Gunawan

Deriving the time-dependent expected reward function associated with a continuous-time Markov chain involves the computation of its transient deviation matrix. In this paper we focus on the special case of a finite quasi-birth-and-death…

Probability · Mathematics 2017-02-10 Sarah Dendievel , Sophie Hautphenne , Guy Latouche , Peter Taylor

We consider forward-backward greedy algorithms for solving sparse feature selection problems with general convex smooth functions. A state-of-the-art greedy method, the Forward-Backward greedy algorithm (FoBa-obj) requires to solve a large…

Machine Learning · Statistics 2014-01-08 Ji Liu , Ryohei Fujimaki , Jieping Ye

Accurate, fine-grained poverty maps remain scarce across much of the Global South. While Demographic and Health Surveys (DHS) provide high-quality socioeconomic data, their spatial coverage is limited and reported coordinates are randomly…

Machine Learning · Computer Science 2025-11-04 Markus B. Pettersson , Adel Daoud

Standard macroeconomic frameworks have correctly identified Japan's government debt - now exceeding 240% of GDP - as carrying substantial fiscal risk. Yet FRED data from 2013 to 2026 present an empirical record inviting a complementary…

Econometrics · Economics 2026-04-21 Hirofumi Wakimoto

We introduce a novel machine learning method called the Penalized Profile Support Vector Machine based on the Gabriel edited set for the computation of the probability of failure for a complex system as determined by a threshold condition…

Machine Learning · Statistics 2026-01-30 Jacob Zhu , Donald Estep