High-Performance Open-Source Archive
Non-parametric methods as local normal regression, polynomial local regression and penalized cubic B-splines regression are used to estimate quantiles curves. See Fan and Gijbels (1996) <doi:10.1201/9780203748725> and Perperoglou et al.(2019) <doi:10.1186/s12874-019-0666-3>.
| Version: | 1.0.0 |
| Imports: | graphics, KernSmooth, locpol, np, quantreg, quantregGrowth, stats |
| Published: | 2022-03-11 |
| DOI: | 10.32614/CRAN.package.quantCurves |
| Author: | Sandie Ferrigno [cre, aut], Dounia Essaket [ctb], Arthur Mouchot [ctb], Hugo Breton [ctb], Myriam Maumy [ctb] |
| Maintainer: | Sandie Ferrigno <sandie.ferrigno at univ-lorraine.fr> |
| License: | CeCILL version 2 | CECILL-2.1 [expanded from: CeCILL] |
| NeedsCompilation: | no |
| CRAN checks: | quantCurves results |
| Reference manual: | quantCurves.html , quantCurves.pdf |
| Package source: | quantCurves_1.0.0.tar.gz |
| Windows binaries: | r-devel: quantCurves_1.0.0.zip, r-release: quantCurves_1.0.0.zip, r-oldrel: quantCurves_1.0.0.zip |
| macOS binaries: | r-release (arm64): quantCurves_1.0.0.tgz, r-oldrel (arm64): quantCurves_1.0.0.tgz, r-release (x86_64): quantCurves_1.0.0.tgz, r-oldrel (x86_64): quantCurves_1.0.0.tgz |
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