Shape-Restricted Regression Splines with R Package splines2

Wenjie Wang ； Jun Yan

《Journal of Data Science》 19卷3期 (2021/07) Pp. 498-517

https://doi.org/10.6339/21-JDS1020

摘要

Splines are important tools for the flexible modeling of curves and surfaces in regression analyses. Functions for constructing spline basis functions are available in R through the base package splines. When the curves to be modeled have known characteristics in monotonicity or curvature, more efficient statistical inferences are possible with shape-restricted splines. Such splines, however, are not available in the R package splines. The package splines2 provides easy-to-use shape-restricted spline basis functions, along with their derivatives and integrals which are important tools in many inference scenarios. It also provides additional splines and features that are not available in the splines package, such as periodic splines and generalized Bernstein polynomials. The usages of the functions are illustrated with shape-restricted regression, recurrent event data analysis, and extreme-value copulas.

關鍵字

Cox-de Boor algorithm ； derivatives ； integrals ； monotone regression ； periodic splines