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...

In this paper, we study the problem of non parametric estimation of the spectral density f of a stationary Gaussian sequence. For this purpose, we consider a collection of finite dimensional linear spaces (e.g. linear space spanned by wavelets or piecewise polynomials on possibly irregular grids...

In the setting of nonparametric hazard estimation under right random censorship by the kernel method, asynmptotic lower bounds for bandwidth selection are provided. If the error criterion is the integrated Squared Error (ISE), and if the distribution function of the underlying lifetime is...

We derive sharp asymptotic minimax bounds (that is, bounds which concern the exact asymptotic constant of the risk) for nonparametric density estimation based on weakly dependent observations. We study two particular problems for which there already exist such results in the case of independent...

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.

Among several concepts encompassed by the idea of an equilibrium rate of unemployment (labour mismatch, unemployment trend, non inflationary unemployment, structural unemployment), the NAIRU appears as the most intereting one for a central bank since it focuses directly on inflation. Thus, the...