Maximum likelihood estimation for small noise multiscale diffusions

Konstantinos Spiliopoulos, Alexandra Chronopoulou

Research output: Contribution to journalArticlepeer-review


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 languageEnglish (US)
Pages (from-to)237-266
Number of pages30
JournalStatistical Inference for Stochastic Processes
Issue number3
StatePublished - Oct 2013
Externally publishedYes


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

ASJC Scopus subject areas

  • Statistics and Probability


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