We consider a kernel based approach to nonlinear canonical correlation analysis and its implementation for time series. We deduce various diagnostics for reversible processes and gaussian processes. The method is first applied to a stimulated series satisfying a diffusion equation allowing us to...

We consider a kernel based approach to nonlinear canonical correlation analysis and its implementation for time series. We deduce a test procedure of the reversibility hypothesis. The method is applied to the analysis of stochastic differential equation from high frequency data on stock returns.

This paper shows how Bayesian inference for switching regression models and their generalisations can be achieved by the specification of loss functions which overcome the label switching problem common to all mixture models. We also derive an extension to models where the number of components...

We establish the validity of an Edgeworth expansion to the distribution of the maximum likelihood estimator of the parameter of a stationary, Gaussian, strongly dependent process. The result covers many types of ARFIMA models.

In this paper, we consider the problem of estimating Switching-regime GARCH Models. The likelihood being in general intractable, we propose an estimation method based on linear representations.

This paper studies under which conditions a cross-section regression yields unbiased estimates of the parameters of an individual dynamic model with fixed effects and individual-specific responses to macro shocks.

We examine the effect if two specific noises (either known or small ones) on a dynamical system. We obtain consistent estimates with their rates of convergence for the invariant density in that context.

We use post-war quarterly data from Belgium, Canada, France, Germany, Greece, Ireland, Japan, theNetherlands, the United Kingdom, and the United States to examine the Fisherian link between inflation and the short-term nominal interest rates.