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Statistical learning for $\psi$-weakly dependent processes
- Publication Year :
- 2022
-
Abstract
- We consider statistical learning question for $\psi$-weakly dependent processes, that unifies a large class of weak dependence conditions such as mixing, association,$\cdots$ The consistency of the empirical risk minimization algorithm is established. We derive the generalization bounds and provide the learning rate, which, on some H{\"o}lder class of hypothesis, is close to the usual $O(n^{-1/2})$ obtained in the {\it i.i.d.} case. Application to time series prediction is carried out with an example of causal models with exogenous covariates.
- Subjects :
- Mathematics - Statistics Theory
Subjects
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2210.00088
- Document Type :
- Working Paper