The study of the time-of-day electricity demand motivates the introduction of a new class of nonparametric estimators: the constrained smoothing spline estimator. We compare the results obtained with this estimator against the classical Fourier and smoothing splines estimates.

We propose a specification test of a parametrically specified model against a weakly specified alternative. The latter is estimated using K nonparametric nearest neighbors (K-NN) in the context of an artificial regression. We derived the asymptotic distribution under the null hypothesis and...

We propose a specification test of a parametrically specified nonlinear model against a weakly specified alternative. We generalize a similar test procedure proposed by Delgado and Stengos (1990) to test the specification of a linear model. We estimate the alternative model by using K...

We develop non-nested tests in a general spatial, spatio-temporal or panel data context. The spatial aspect can be interpreted quite generally, in either a geographical sense, or employing notions of economic distance, or even when parametric modelling arises in part from a common factor or...

We develop non-nested tests in a general spatial, spatio-temporal or panel data context. The spatial aspect can be interpreted quite generally, in either a geographical sense, or employing notions of economic distance, or when parametric modelling arises in part from a common factor or other...

This article proposes a class of goodness-of-fit tests for the autocorrelation function of a time series process, including those exhibiting long-range dependence. Test statistics for composite hypotheses are functionals of a (approximated) martingale transformation of the Bartlett’s...

We develop non-nested tests in a general spatial, spatio-temporal or panel data context. The spatial aspect can be interpreted quite generally, in either a geographical sense, or employing notions of economic distance, or even when parametric modelling arises in part from a common factor or...

This paper proposes a test statistic for discriminating between two partly non-linear regression models whose parametric components are non-nested. The statistic has the form of a J-test based on a parameter which artificially nests the null and alternative hypotheses. We study in detail the...

A test for serial independence of regression errors is proposed that is consistent in the direction ofserial dependence alternatives of first order. The test statistic is a function of aHoeffding-Blum-Kiefer-Rosenblatt type of empirical process, based on residuals. The resultantstatistic...

We propose a specification test of a parametrically specified nonlinear model against a weakly specified alternative. We generalize a similar test procedure proposed by Delgado and Stengos (1990) to test the specification of a linear model. We estimate the alternative model by using K...