Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
npbr: A Package for Nonparametric Boundary Regression in R | Daouia | Journal of Statistical Software
Authors: Abdelaati Daouia, Thibault Laurent, Hohsuk Noh
Title: npbr: A Package for Nonparametric Boundary Regression in R
Abstract: The package npbr is the first free specialized software for data edge and frontier analysis in the statistical literature. It provides 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 single and multiple shape constraints. They also cover data envelopment techniques as well as robust approaches to outliers. The routines included in npbr are user friendly and afford a large degree of flexibility in the estimation specifications. They provide smoothing parameter selection for the modern local linear and polynomial spline methods as well as for some promising extreme value techniques. Also, they seamlessly allow for Monte Carlo comparisons among the implemented estimation procedures. This package will be very useful for statisticians and applied researchers interested in employing nonparametric boundary regression models. Its use is illustrated with a number of empirical applications and simulated examples.

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Paper: npbr: A Package for Nonparametric Boundary Regression in R     Download PDF (Downloads: 365)
Supplements:
npbr_1.6.tar.gz: R source package Download (Downloads: 39; 1MB)
v79i09.R: R replication code Download (Downloads: 58; 26KB)

DOI: 10.18637/jss.v079.i09

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.