fastlpr: Fast Local Polynomial Regression and Kernel Density Estimation
Non-Uniform Fast Fourier Transform ('NUFFT')-accelerated local polynomial
regression and kernel density estimation for large, scattered, or
complex-valued datasets. Provides automatic bandwidth selection via
Generalized Cross-Validation (GCV) for regression and Likelihood
Cross-Validation (LCV) for density estimation. This is the 'R' port of the
'fastLPR' 'MATLAB'/'Python' toolbox, achieving O(N + M log M) computational
complexity through custom 'NUFFT' implementation with Gaussian gridding.
Supports 1D/2D/3D data, complex-valued responses, heteroscedastic variance
estimation, and confidence interval computation. Performance optimized with
vectorized 'R' code and compiled helpers via 'Rcpp'/'RcppArmadillo'.
Extends the 'FKreg' toolbox of Wang et al. (2022)
<doi:10.48550/arXiv.2204.07716> with 'Python' and 'R' ports. Applied in
Li et al. (2022) <doi:10.1016/j.neuroimage.2022.119190>. Uses 'NUFFT'
methods based on Greengard and Lee (2004) <doi:10.1137/S003614450343200X>,
binning-accelerated kernel estimation of Wand (1994)
<doi:10.1080/10618600.1994.10474656>, and local polynomial regression
framework of Fan and Gijbels (1996, ISBN:978-0412983214).
| Version: |
1.0.1 |
| Depends: |
R (≥ 4.2.0) |
| Imports: |
stats, utils, grDevices, graphics, compiler, Rcpp (≥ 1.0.0) |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
testthat (≥ 3.0.0), akima, rgl, R.matlab |
| Published: |
2026-04-21 |
| DOI: |
10.32614/CRAN.package.fastlpr (may not be active yet) |
| Author: |
Ying Wang [aut, cre],
Min Li [aut] |
| Maintainer: |
Ying Wang <yingwangrigel at gmail.com> |
| BugReports: |
https://github.com/rigelfalcon/fastLPR/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/rigelfalcon/fastLPR |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make |
| Citation: |
fastlpr citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
fastlpr results |
Documentation:
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