Stochastic Systems

Moderate deviations for recursive stochastic algorithms

Paul Dupuis and Dane Johnson

Full-text: Open access

Abstract

We prove a moderate deviation principle for the continuous time interpolation of discrete time recursive stochastic processes. The methods of proof are somewhat different from the corresponding large deviation result, and in particular the proof of the upper bound is more complicated.

Article information

Source
Stoch. Syst., Volume 5, Number 1 (2015), 87-119.

Dates
Received: January 2014
First available in Project Euclid: 23 December 2015

Permanent link to this document
https://projecteuclid.org/euclid.ssy/1450879282

Digital Object Identifier
doi:10.1214/14-SSY138

Mathematical Reviews number (MathSciNet)
MR3442390

Zentralblatt MATH identifier
1335.60050

Subjects
Primary: 60F10: Large deviations 60J05: Discrete-time Markov processes on general state spaces
Secondary: 60F17: Functional limit theorems; invariance principles

Keywords
Large deviations moderate deviations weak convergence

Citation

Dupuis, Paul; Johnson, Dane. Moderate deviations for recursive stochastic algorithms. Stoch. Syst. 5 (2015), no. 1, 87--119. doi:10.1214/14-SSY138. https://projecteuclid.org/euclid.ssy/1450879282


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