We determine optimal designs for some regression models which are frequently used for describing 3D shapes. These … information matrix in the spherical harmonic regression model as the uniform distribution and are therefore directly implementable …

The purpose of this paper is to propose a procedure for testing the equality of several regression curves fi in … nonparametric regression models when the noise is inhomogeneous. This extends work of Dette and Neumeyer (2001) and it is shown that … maximum likelihood statistic from a heteroscedastic one way ANOVA to the context of nonparametric regression. The maximum …

In this paper it is shown that the number of latent factors in a multiple multivariate regression model need not be …

common linear and nonparametric regression model, which are based on empirical processes of residuals. It is well known that … linear and nonparametric regression models. …

In this paper we present a detailed numerical comparison of three monotone nonparametric kernel regression estimates … Pilz (2003) and combines density and regression estimation techniques to obtain a monotone curve estimate of the inverse of … the isotone regression function. The three concepts are briefly reviewed and their finite sample properties are studied by …

A monotone estimate of the conditional variance function in a heteroscedastic, nonpara- metric regression model is …

In this note we consider several goodness-of-fit tests for model specification in non- parametric regression models … asymptotically optimal bandwidth for the estimation of the regression function. We prove weak convergence of these processes to …

. In this paper we describe a program to use this approach based on a combination of multinomial logistic regression and … [epsilon]-support vector regression from modern statistical machine learning. …