npbr: Nonparametric Boundary Regression

A variety of functions for the best known and most innovative approaches to nonparametric boundary estimation. The selected methods are concerned with empirical, smoothed, unrestricted as well as constrained fits under both separate and multiple shape constraints. They cover robust approaches to outliers as well as data envelopment techniques based on piecewise polynomials, splines, local linear fitting, extreme values and kernel smoothing. The package also seamlessly allows for Monte Carlo comparisons among these different estimation methods. Its use is illustrated via a number of empirical applications and simulated examples.

Version:	1.8
Depends:	R (≥ 4.0.0), graphics, stats, utils
Imports:	Benchmarking, np, quadprog, Rglpk (≥ 0.6-2), splines
Published:	2023-03-22
DOI:	10.32614/CRAN.package.npbr
Author:	Abdelaati Daouia, Thibault Laurent, Hohsuk Noh
Maintainer:	Thibault Laurent <thibault.laurent at univ-tlse1.fr>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
Citation:	npbr citation info
CRAN checks:	npbr results

Documentation:

Reference manual:	npbr.pdf
Vignettes:	Non parametric

Downloads:

Package source:	npbr_1.8.tar.gz
Windows binaries:	r-devel: npbr_1.8.zip, r-release: npbr_1.8.zip, r-oldrel: npbr_1.8.zip
macOS binaries:	r-release (arm64): npbr_1.8.tgz, r-oldrel (arm64): npbr_1.8.tgz, r-release (x86_64): npbr_1.8.tgz, r-oldrel (x86_64): npbr_1.8.tgz
Old sources:	npbr archive

Linking:

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