The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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 |
| 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 |
| Reference manual: | fastlpr.html , fastlpr.pdf |
| Package source: | fastlpr_1.0.1.tar.gz |
| Windows binaries: | r-devel: fastlpr_1.0.1.zip, r-release: fastlpr_1.0.1.zip, r-oldrel: fastlpr_1.0.1.zip |
| macOS binaries: | r-release (arm64): fastlpr_1.0.1.tgz, r-oldrel (arm64): fastlpr_1.0.1.tgz, r-release (x86_64): fastlpr_1.0.1.tgz, r-oldrel (x86_64): fastlpr_1.0.1.tgz |
Please use the canonical form https://CRAN.R-project.org/package=fastlpr to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.