Triogram Models
本文提出Triogram方法，基于自适应三角剖分用分段线性双变量样条估计函数，适用于双变量回归和对数密度估计，且对仿射变换不变。
Abstract In this article we introduce the Triogram method for function estimation using piecewise linear, bivariate splines based on an adaptively constructed triangulation. We illustrate the technique for bivariate regression and log-density estimation and indicate how our approach can be applied directly to model bivariate functions in the broader context of an extended linear model. The entire estimation procedure is invariant under affine transformations and is a natural approach for modeling data when the domain of the predictor variables is a polygonal region in the plane. Although our examples deal exclusively with estimating bivariate functions, the use of Triograms for modeling two-factor interactions in analysis of variance decompositions of functions depending on more than two variables is straightforward.