taylerablake/thin-plate-splines: Smoothing Splines for Large Samples
Version 1.1-0

Fits smoothing spline regression models using scalable algorithms designed for large samples. Seven marginal spline types are supported: linear, cubic, different cubic, cubic periodic, cubic thin-plate, ordinal, and nominal. Random effects and parametric effects are also supported. Response can be Gaussian or non-Gaussian: Binomial, Poisson, Gamma, Inverse Gaussian, or Negative Binomial.

Getting started

Package details

AuthorNathaniel E. Helwig <[email protected]>
Date of publication2017-02-03 14:32:57
MaintainerNathaniel E. Helwig <[email protected]>
LicenseGPL (>= 2)
Version1.1-0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("taylerablake/thin-plate-splines")
taylerablake/thin-plate-splines documentation built on Sept. 19, 2017, 9:45 a.m.