snfa: Smooth Non-Parametric Frontier Analysis

Fitting of non-parametric production frontiers for use in efficiency analysis. Methods are provided for both a smooth analogue of Data Envelopment Analysis (DEA) and a non-parametric analogue of Stochastic Frontier Analysis (SFA). Frontiers are constructed for multiple inputs and a single output using constrained kernel smoothing as in Racine et al. (2009), which allow for the imposition of monotonicity and concavity constraints on the estimated frontier.

Version: 0.0.1
Depends: R (≥ 3.5.0)
Imports: abind (≥ 1.4.5), ggplot2 (≥ 3.1.0), prodlim (≥ 2018.4.18), quadprog (≥ 1.5.5), Rdpack (≥ 0.10.1), rootSolve (≥ 1.7)
Published: 2018-12-01
DOI: 10.32614/CRAN.package.snfa
Author: Taylor McKenzie [aut, cre]
Maintainer: Taylor McKenzie <tkmckenzie at gmail.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: snfa results

Documentation:

Reference manual: snfa.html , snfa.pdf

Downloads:

Package source: snfa_0.0.1.tar.gz
Windows binaries: r-devel: snfa_0.0.1.zip, r-release: snfa_0.0.1.zip, r-oldrel: snfa_0.0.1.zip
macOS binaries: r-release (arm64): snfa_0.0.1.tgz, r-oldrel (arm64): snfa_0.0.1.tgz, r-release (x86_64): snfa_0.0.1.tgz, r-oldrel (x86_64): snfa_0.0.1.tgz

Linking:

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