Kernel Functional Partial Least Squares
Overview
Implementation for kernel functional partial least squares (KFPLS) method. KFPLS method is developed for functional nonlinear models, and the method does not require strict constraints for the nonlinear structures. The crucial function of this package is KFPLS().
Install
Health
NOTEdependencies in R coder-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Namespace in Imports field not imported from: ‘splines’ All declared Imports should be used.
- NOTE11 OK, 2 NOTE2026-06-09
- ERROR10 OK, 2 NOTE, 1 ERROR2026-06-08
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 2
- Examples that run
- 100%1 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Installing KFPLS adds 37 packages (23 with compiled code, 32 MB of source tarballs). Heaviest: ggplot2 6.0 MB, fds 3.7 MB, mclust 2.7 MB.
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 1.0Latest2023-01-10 · current release
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2023-01-10
- Total releases
- 1 / 3 yrs
- License
- GPL (>= 3) OSI
- Download size
- 4.4 KB
Cite
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Run in R for the authors' preferred citation:
citation("KFPLS")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
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