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jackstrap

Correcting Nonparametric Frontier Measurements for Outliers

v0.1.0 · Jun 9, 2020 · GPL-3

Description

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>.

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dependencies in R code

Namespaces in Imports field not imported from:
  ‘fBasics’ ‘reshape’ ‘tidyr’ ‘utils’
  All declared Imports should be used.
NOTE r-devel-linux-x86_64-fedora-gcc

dependencies in R code

Namespaces in Imports field not imported from:
  ‘fBasics’ ‘reshape’ ‘tidyr’ ‘utils’
  All declared Imports should be used.

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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
NOTE r-devel-linux-x86_64-fedora-clang

dependencies in R code

Namespaces in Imports field not imported from:
  ‘fBasics’ ‘reshape’ ‘tidyr’ ‘utils’
  All declared Imports should be used.
NOTE r-devel-linux-x86_64-fedora-gcc

dependencies in R code

Namespaces in Imports field not imported from:
  ‘fBasics’ ‘reshape’ ‘tidyr’ ‘utils’
  All declared Imports should be used.

Dependency Network

Dependencies Reverse dependencies fBasics Benchmarking dplyr ggplot2 foreach doParallel reshape tidyr scales plyr rlang jackstrap

Version History

1 tracked
new 0.1.0 Mar 10, 2026

R Observatory began tracking this package on Mar 10, 2026; it first appeared on CRAN Jun 9, 2020. Releases before tracking aren’t shown.