Nonparametric regression techniques provide an e ective way of identifying and examiningstructure in regression data The standard approaches to nonparametric regression suchas local polynomial and smoothing spline estimators are sensitive to unusual observations and alternatives designed to be...

In this paper we consider the estimation of a density f on the basis of random sample from a weighted distribution G with density g given by g(x) = w(x)f(x)/ Atilde; Acirc;micro;w, where w(u)gt;0 for all u and Atilde; Acirc;micro;w = Atilde;cent;Acirc; Acirc;laquo; w(u)f(u)du lt; Atilde;cent;Acirc; Acirc; . A...

An improved AIC-based criterion is derived for model selection in general smoothing-basedmodeling, including semiparametric models and additive models. Examples areprovided of applications to goodness-of-fit, smoothing parameter and variable selectionin an additive model and semiparametric...

We consider a common components model for multivariate fractional cointegration, in which the s cedil; 1 components have different memory parameters. The cointegrating rank is allowed to exceed 1. The true cointegrating vectors can be decomposed into orthogonal fractional cointegrating subspaces...

We consider a fractional exponential, or FEXP estimator of the memory parameter of a stationary Gaussian long-memory time series. The estimator is constructed by fitting a FEXP model of slowly increasing dimension to the log periodogram at all Fourier frequencies by ordinary least squares, and...

We study the properties of MallowsAtilde;cent;Acirc; Acirc; CL criterion for selecting a fractional exponential (FEXP) model for a Gaussian long-memory time series. The aim is to minimize the mean squared error of a corresponding regression estimator dFEXP of the memory parameter, d. Under...