In this paper we study time-varying coefficient (beta coefficient) models with a time trend function to characterize the nonlinear, non-stationary and trending phenomenon in time series and to explain the behavior of asset returns. The general local polynomial method is developed to estimate the...

In this article, we propose a new canonical correlation method based on information theory. This method examines potential nonlinear relationships between px1 vector Y-set and qx1 vector X-set. It finds canonical coefficient vectors a and b by maximizing a more general measure, the mutual...

In this article, for the regression mean function of Y on , where Y is a scalar, is a px1 vector and W is a categorical variable, we propose a method, partial sparse MAVE, to achieve sufficient dimension reduction and variable selection on simultaneously. The method relaxes any particular...

We show that the test statistic for dimension in q-based principal Hessian directions (pHd) is distributed as a linear combination of [chi]2 random variables. Simpler distributions can result depending on the distribution of the predictors and the adequacy of the quadratic model.

Yin and Cook [2002. Dimension reduction for the conditional k-th moment in regression. J. Roy. Statist. Soc. B 64, 159-175] established a general equivalence between sliced inverse regression (sir) and a marginal moment method called Covk. In this note, we form a new marginal method called phdk...