In parametric regression problems, estimation of the parameter of interest is typically achieved via the solution of a set of unbiased estimating equations. We are interested in problems where in addition to this parameter, the estimating equations consist of an unknown nuisance function which...

This paper shows the uniform consistency in probability of modified kernel estimators towards the Baire functions representing the conditional variances and contemporaneous conditional covariances provided the data generating process is given by a strictly stationary solution of a nonparametric...

This paper shows the uniform consistency in probability of a modified kernel estimator towards the Baire function representing the conditional variance provided the data generating process is given by a strictly stationary solution of a parametric ARCH(q)- model.