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Kernel-penalized regression

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The KPR package provides estimation and inference methods for kernel-penalized regression models, designed for doubly-structured high dimensional data. An explanation of the theory and usage of kernel-penalized regression can be found here.

Installation

Install with devtools::install_github("pknight24/KPR")

Usage

Model fitting is performed with the KPR() function.

kpr.out <- KPR(X = X, Y = Y, H = H, Q = Q)

The kpr.out object has class KPR and includes all of the data used to fit the model, as well as coefficient estimates and tuning parameters.

The package also provides support for variable selection using the GMD inference.

kpr.out <- inference(kpr.out)

This new kpr.out object also contains a list of p-values corresponding to each variable in the model.

For a more detailed example, see the vignette.