Package: jackstrap 0.1.0

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>.

Authors:Kleber Morais de Sousa [aut, cre], Maria da Conceicao Sampaio de Sousa [aut], Paulo Aguiar do Monte [aut]

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NEWS

# Install 'jackstrap' in R:
install.packages('jackstrap', repos = c('https://klebermsousa.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/klebermsousa/jackstrap/issues

Datasets:

On CRAN:

deajackstrapnonparametricoutlier-detection

3.85 score 1 stars 14 scripts 146 downloads 6 exports 53 dependencies

Last updated 4 years agofrom:9a01fb50fa. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 15 2024
R-4.5-winNOTENov 15 2024
R-4.5-linuxNOTENov 15 2024
R-4.4-winNOTENov 15 2024
R-4.4-macNOTENov 15 2024
R-4.3-winNOTENov 15 2024
R-4.3-macNOTENov 15 2024

Exports:hist_jack_kshist_jack_stepjackstrapjackstrap_ksplot_jackstrap_kssummary_jackstrap

Dependencies:Benchmarkingclicodetoolscolorspacecpp11doParalleldplyrfansifarverfBasicsforeachgenericsggplot2gluegssgtableisobanditeratorslabelinglatticelifecyclelpSolveAPImagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrpurrrquadprogR6RColorBrewerRcppreshaperlangscalesspatialstablediststringistringrtibbletidyrtidyselecttimeDatetimeSeriesucminfutf8vctrsviridisLitewithr

Jackstrap

Rendered fromjackstrap.Rmdusingknitr::rmarkdownon Nov 15 2024.

Last update: 2020-05-12
Started: 2020-05-12