Statistical learning for $$\psi $$ ψ -weakly dependent processes

Mamadou Lamine Diop () and William Kengne ()
Additional contact information
Mamadou Lamine Diop: Université Gaston Berger
William Kengne: Universite Claude Bernard Lyon 1

Statistical Inference for Stochastic Processes, 2025, vol. 28, issue 2, No 5, 23 pages

Abstract: Abstract The purpose of this paper is to study the generalization performance of the Empirical Risk Minimization (ERM) algorithm from $$\psi $$ ψ -weakly dependent processes. These processes unify a large class of weak dependence conditions, including strong mixing and association. We first establish the exponential bound on the rate of relative uniform convergence and the consistency of the ERM algorithm. Secondly, we derive generalization bounds and provide the learning rate. Under some Hölder class of hypothesis, we obtain an asymptotic rate close to $$O(n^{-1/2})$$ O ( n - 1 / 2 ) . Finally, we present some application and simulation results with examples of causal models within the context of time series prediction.

Keywords: Generalization performance; $$\psi $$ ψ -weak dependence; ERM algorithm; Generalization bounds; Consistent (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11203-025-09329-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sistpr:v:28:y:2025:i:2:d:10.1007_s11203-025-09329-6

Ordering information: This journal article can be ordered from
http://www.springer. ... ty/journal/11203/PS2

DOI: 10.1007/s11203-025-09329-6

Access Statistics for this article

Statistical Inference for Stochastic Processes is currently edited by Denis Bosq, Yury A. Kutoyants and Marc Hallin

More articles in Statistical Inference for Stochastic Processes from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().