Nothing
bigsplines: Smoothing Splines for Large Samples
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
Browse package contents
Package details |
|
|---|---|
| Author | Nathaniel E. Helwig <helwig@umn.edu> |
| Maintainer | Nathaniel E. Helwig <helwig@umn.edu> |
| License | GPL (>= 2) |
| Version | 1.1-1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the bigsplines package in your browser
Any scripts or data that you put into this service are public.
