We focus on the construction of confidence corridors for multivariate nonparametric generalized quantile regression functions. This construction is based on asymptotic results for the maximal deviation between a suitable nonparametric estimator and the true function of interest which follow...

In this paper we describe a solution to the problem of controlling the size of homoskedasticity tests in linear regression contexts.

Non parametric and parametric estimation for the spectral density of a stationary process is a well-known topic, except when the spectrum vanishes for some frequency. Indeed, for this frequency, the limit law degenerates, and traditional inference no longer applies. The paper introduces non...

It is well-known that traditional inference do not apply when the spectral density of a stationary process vanishes for some frequency. This paper examines some properties of several new non parametric tests of this hypothesis which have been recently proposed by Lacroix (1999). These tests...

Fractionally integrated processes have become a standard class of models to describe the long memory features of economic and financial time series data. However, it has been demonstrated in numerous studies that structural break processes and non-linear features can often be confused as being...

The paper considers the use of artiï¬cial regression in calculating different types of score test when the logâˆ'likelihood is based on probabilities rather than densities. The calculation of the information matrix test is also considered. Results are specialised to deal with binary...

This research reflects the importance in statistics of the territorial indexes numbers which express the dynamic of the statistical variables in territorial profile. The purpose of this paper consists in to reflect over of the economic life, how we will can to apply some important...

In this paper we consider the problem of testing the null hypothesis that a series has a constant level against the alternative that the level follows a random walk. This problem has previously been studied by inter alia, Nyblom and Makelainen in the context of the orthogonal random walk plus...

In this paper, we consider the problem of estimation of semi-linear regression models. Using invariance arguments, Bhowmik and King (2001) have derived the probability density functions of the maximal invariant statistic for the nonlinear component of these models. Using these density functions...

In the context of a general regression model in which some regression coefficients are of interest and others are purely nuisance parameters, we derive the density function of a maximal invariant statistic with the aim of testing for the inclusion of regressors (either linear or non-linear) in...