Maximum likelihood estimation for small noise multiscale diffusions

Konstantinos Spiliopoulos; Alexandra Chronopoulou

doi:10.1007/s11203-013-9088-8

Maximum likelihood estimation for small noise multiscale diffusions

Konstantinos Spiliopoulos, Alexandra Chronopoulou

Research output: Contribution to journal › Article

Abstract

We study the problem of parameter estimation for stochastic differential equations with small noise and fast oscillating parameters. Depending on how fast the intensity of the noise goes to zero relative to the homogenization parameter, we consider three different regimes. For each regime, we construct the maximum likelihood estimator and we study its consistency and asymptotic normality properties. A simulation study for the first order Langevin equation with a two scale potential is also provided.

Original language	English (US)
Pages (from-to)	237-266
Number of pages	30
Journal	Statistical Inference for Stochastic Processes
Volume	16
Issue number	3
DOIs	https://doi.org/10.1007/s11203-013-9088-8
State	Published - Oct 1 2013
Externally published	Yes

Keywords

Central limit theorem
Dynamical systems
Multiscale diffusions
Parameter estimation
Rough energy landscapes

ASJC Scopus subject areas

Statistics and Probability

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Spiliopoulos, K., & Chronopoulou, A. (2013). Maximum likelihood estimation for small noise multiscale diffusions. Statistical Inference for Stochastic Processes, 16(3), 237-266. https://doi.org/10.1007/s11203-013-9088-8

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