jackstrap: Correcting Nonparametric Frontier Measurements for Outliers

Provides method used to check whether data have outlier in efficiency measurement of big samples with data envelopment analysis (DEA). In this jackstrap method, the package provides two criteria to define outliers: heaviside and k-s test. The technique was developed by Sousa and Stosic (2005) "Technical Efficiency of the Brazilian Municipalities: Correcting Nonparametric Frontier Measurements for Outliers." <doi:10.1007/s11123-005-4702-4>.

Version: 0.1.0
Depends: R (≥ 2.15.1)
Imports: fBasics, Benchmarking, dplyr, ggplot2, foreach, doParallel, reshape, tidyr, scales, parallel, graphics, plyr, rlang, utils
Suggests: knitr, rmarkdown
Published: 2020-06-09
DOI: 10.32614/CRAN.package.jackstrap
Author: Kleber Morais de Sousa [aut, cre], Maria da Conceicao Sampaio de Sousa [aut], Paulo Aguiar do Monte [aut]
Maintainer: Kleber Morais de Sousa <kleberfinancas at gmail.com>
License: GPL-3
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: jackstrap results


Reference manual: jackstrap.pdf
Vignettes: Put the title of your vignette here


Package source: jackstrap_0.1.0.tar.gz
Windows binaries: r-devel: jackstrap_0.1.0.zip, r-release: jackstrap_0.1.0.zip, r-oldrel: jackstrap_0.1.0.zip
macOS binaries: r-release (arm64): jackstrap_0.1.0.tgz, r-oldrel (arm64): jackstrap_0.1.0.tgz, r-release (x86_64): jackstrap_0.1.0.tgz, r-oldrel (x86_64): jackstrap_0.1.0.tgz


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