Entropy estimation and information theory form the bedrock of our understanding of uncertainty and complexity in both natural and engineered systems. At its core, entropy quantifies the ...

We propose a nonparametric estimation theory for the occupation density, the drift vector, and the diffusion matrix of multivariate diffusion processes. The estimators are sample analogues to ...

Nonparametric identification and maximum likelihood estimation for finite-state hidden Markov models are investigated. We obtain identification of the parameters as well as the order of the Markov ...