This paper provides methods for carrying out likelihood based inference for diffusion driven models, for example discretely observed multivariate diffusions, continuous time stochastic volatility models and counting process models. The diffusions can potentially be non-stationary. Although our...

The paper is devoted to investigation of a number of difference-differential equations, among them the following one plays the central role: dFn/dt=φ(Fn)(Fn-1 - Fn) (*) where, for every t, {Fn(t), n = 0, 1, 2, ...} is a probability distribution function, and φ is a positive function on [0, 1]....