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quantCurves
View on CRAN: Click
here
Download and install quantCurves package within the R console
Install from CRAN:
install.packages("quantCurves")
Install from Github:
library("remotes")
install_github("cran/quantCurves")
Install by package version:
library("remotes")
install_version("quantCurves", "1.0.0")
Attach the package and use:
library("quantCurves")
Maintained by
Sandie Ferrigno
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.quantCurves . quantCurves results . quantCurves.pdf . quantCurves_1.0.0.tar.gz . quantCurves_1.0.0.zip . quantCurves_1.0.0.zip . quantCurves_1.0.0.zip . quantCurves_1.0.0.tgz . quantCurves_1.0.0.tgz . quantCurves_1.0.0.tgz . quantCurves_1.0.0.tgz . https://CRAN.R-project.org/package=quantCurves .
First Published: 2022-03-11
Latest Update: 2022-03-11
Description:
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) and Perperoglou et al.(2019) .
How to cite:
Sandie Ferrigno (2022). quantCurves: Estimate Quantiles Curves. R package version 1.0.0, https://cran.r-project.org/web/packages/quantCurves. Accessed 29 Apr. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited quantCurves R package
View quantCurves citation profile
Other R packages that quantCurves depends,
imports, suggests or enhances
Complete documentation for quantCurves
Functions, R codes and Examples using
the quantCurves R package
Some associated functions: CentCurv . bSplinesData . bandwidth . bsplines . compareCurv . fourCurv . locNormCst . locNormCstData . locNormLin . locNormLinData . polylocLin . polylocLinData .
Some associated R codes: Bsplines.R . CentCurv.R . bandwidth.R . compareCurv.R . fourCurv.R . locNormCst.R . locNormLin.R . polylocLin.R . Full quantCurves package functions and examples
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