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snfa (version 0.0.1)

Smooth Non-Parametric Frontier Analysis

Description

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.

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Version

Install

install.packages('snfa')

Monthly Downloads

147

Version

0.0.1

License

GPL-3

Maintainer

Taylor McKenzie

Last Published

December 1st, 2018

Functions in snfa (0.0.1)

technical.efficiency.change

Technical and efficiency change estimation
H.inv.select

Bandwidth matrix selection
USMacro

US Macroeconomic Data
fit.mean

Kernel smoothing with additional constraints
fit.sf

Non-parametric stochastic frontier
panel.production

Randomly generated panel of production data
reflect.data

Data reflection for kernel smoothing
allocative.efficiency

Allocative efficiency estimation
fit.boundary

Multivariate smooth boundary fitting with additional constraints
univariate

Randomly generated univariate data