Characteristic function estimation of non-Gaussian Ornstein–Uhlenbeck processes

Parameter estimation for non-Gaussian autoregressive processes

It is proposed to jointly estimate the parameters of nonGaussian autoregressive (AR) processes in a Bayesian context using the Gibbs sampler. Using the Markov chains produced by the sampler an approximation to the vector MAP estimator is implemented. The results reported here used AR(4) models driven by noise sequences where each sample is iid as a two component Gaussian sum mixture. The result...

Estimation of Continuous Time Processes Via the Empirical Characteristic Function

This paper examines a particular class of continuous-time stochastic processes commonly known as af¿ne diffusions (AD) and af¿ne jump-diffusions (AJD) in which the drift, the diffusion and the jump coef¿cients are all af¿ne functions of the state variables. By deriving the joint characteristic function associated with a vector of observed state variables for such models, we are able to examine ...

Sequential Parameter Estimation of Time-Varying Non-Gaussian Autoregressive Processes

Parameter estimation of time-varying non-Gaussian autoregressive processes can be a highly nonlinear problem. The problem gets even more difficult if the functional form of the time variation of the process parameters is unknown. In this paper, we address parameter estimation of such processes by particle filtering, where posterior densities are approximated by sets of samples (particles) and p...

Efficient estimation of parameters for non-Gaussian autoregressive processes

Anisotropic Function Estimation Using Multi-bandwidth Gaussian Processes.

In nonparametric regression problems involving multiple predictors, there is typically interest in estimating an anisotropic multivariate regression surface in the important predictors while discarding the unimportant ones. Our focus is on defining a Bayesian procedure that leads to the minimax optimal rate of posterior contraction (up to a log factor) adapting to the unknown dimension and anis...