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 |
Author: |
Taylor McKenzie [aut, cre] |
Maintainer: |
Taylor McKenzie <tkmckenzie at gmail.com> |
License: |
GPL-3 |
NeedsCompilation: |
no |
CRAN checks: |
snfa results |
Documentation:
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