The concept of nonparametric smoothing is a central idea in statistics that aims to simultaneously estimate and modes the underlyingstructure. The book considers high dimensional objects, as density functions and regression. The semiparametric modeling technique compromises the two aims,...

The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between...

We consider a generalized partially linear model E(Y|X,T) = G{X'b + m(T)} where G is a known function, b is an unknown parameter vector, and m is an unknown function. The paper introduces a test statistic which allows to decide between a parametric and a semiparametric model: (i) m is linear,...