WE consider a particular type of randomly observed continuous time process, in accordance with the characteristics of dataset coming from financial markets. We adapt the concept of Local Time by defining from the discrete observations an Empirical Local Time and we prove it converges under...

In competing risks model, several failure times arise potentially. The smallest failure time and its index only are observed. In this paper, nonparametric kernel estimators of the joint distribution function of failure times conditional on the covariates are proposed. Their weak or strong...

In 1990, Hjort introduced nonparametric Bayes estimators of the cumulative distribution function and the cumulative hazard rate, based on type I censored data. Our aim in this paper is to study their large sample behaviour. Firstly, we develop a martingale structure for each estimator. Then, we...

We decompose a stationary Markov process (X^t) as: X^t = a^o + [Sommation from j=1 to infinity) a^j Z^(j,t), where the Z^j 's processes admit ARMA specifications. These decompositions are deduced from a nonlinear canonical decomposition of the joint distribution of (X^t, X^(t-1)).

In a nonlinear framework the magnitude of temporal dependence may depend on the transformation applied to time series. The aim of this paper is to examine in detail various forms of persistence and the corresponding transformations. For multivariate series the persistence analysis is used to...

Empirical demand systems that do not impose unreasonable restrictions on preferences are typically nonlinear. For empirical purposes, exact estimation of nonlinear equation systems for large data sets with more than a small number of equations has typically been limited by nonlinearities in the...

We study inference in continuous and discrete processes and propose new estimation procedures. Our approach consists on truncating the initial process what simplifies the estimation while preventing all relevant properties of the infinitesimal generator. For diffusion processes, nonparametric...

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 introduce a class of nonlinear dynamic processes, called compound au- toregressive (CAR), and characterized by the conditional log-Laplace trans- forms which are aÆne functions of the lagged values of the process. The CAR processes resemble the linear autoregressive processes in that their...

In this paper, I explore the ability-earnings relationships semiparametrically. I find evidence of nonlinearities in these relationships which vary across levels of schooling, and argue that ability-sorting into higher education creates problems for accurately identifing the return to schooling...