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KSPM  

Kernel Semi-Parametric Models
View on CRAN: Click here


Download and install KSPM package within the R console
Install from CRAN:
install.packages("KSPM")

Install from Github:
library("remotes")
install_github("cran/KSPM")

Install by package version:
library("remotes")
install_version("KSPM", "0.2.1")



Attach the package and use:
library("KSPM")
Maintained by
Catherine Schramm
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-01-09
Latest Update: 2020-08-10
Description:
To fit the kernel semi-parametric model and its extensions. It allows multiple kernels and unlimited interactions in the same model. Coefficients are estimated by maximizing a penalized log-likelihood; penalization terms and hyperparameters are estimated by minimizing leave-one-out error. It includes predictions with confidence/prediction intervals, statistical tests for the significance of each kernel, a procedure for variable selection and graphical tools for diagnostics and interpretation of covariate effects. Currently it is implemented for continuous dependent variables. The package is based on the paper of Liu et al. (2007), .
How to cite:
Catherine Schramm (2019). KSPM: Kernel Semi-Parametric Models. R package version 0.2.1, https://cran.r-project.org/web/packages/KSPM. Accessed 05 Oct. 2026.
Previous versions and publish date:
0.1.0 (2019-01-09 18:30), 0.1.1 (2019-02-01 18:33), 0.1.2 (2019-04-07 12:12), 0.2.0 (2019-10-14 12:10), (2026-07-09 08:07)
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Complete documentation for KSPM
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