cpr: An R Package For Finding Parsimonious B-Spline Regression Models
via Control Polygon Reduction and Control Net Reduction
release_nh5r65irnbgrjpzkqo6wweqfpu
by
Peter E. DeWitt, Samantha MaWhinney, Nichole E. Carlson
2017
Abstract
The R package cpr provides tools for selection of parsimonious B-spline
regression models via algorithms coined `control polygon reduction' (CPR) and
`control net reduction' (CNR). B-Splines are commonly used in regression models
to smooth data and approximate unknown functional forms. B-Splines are defined
by a polynomial order and a knot sequence. Defining the knot sequence is
non-trivial, but is critical with respect to the quality of the regression
models. The focus of the CPR and CNR algorithms is to reduce a large knot
sequence down to a parsimonious collection of elements while maintaining a high
quality of fit. The algorithms are quick to implement and are flexible enough
to support many types of data and regression approaches. The cpr package
provides the end user collections of tools for the construction of B-spline
basis matrices, construction of control polygons and control nets, and the use
of diagnostics of the CPR and CNR algorithms.
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