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DJL: Distance Measure Based Judgment and Learning

Implements various decision support tools related to the Econometrics & Technometrics. Subroutines include correlation reliability test, Mahalanobis distance measure for outlier detection, combinatorial search (all possible subset regression), non-parametric efficiency analysis measures: DDF (directional distance function), DEA (data envelopment analysis), HDF (hyperbolic distance function), SBM (slack-based measure), and SF (shortage function), benchmarking, Malmquist productivity analysis, risk analysis, technology adoption model, new product target setting, network DEA, dynamic DEA, intertemporal budgeting, etc.

Version: 3.9
Depends: R (≥ 3.4.0), car, lpSolveAPI
Published: 2023-03-16
DOI: 10.32614/CRAN.package.DJL
Author: Dong-Joon Lim, Ph.D. <technometrics.org>
Maintainer: Dong-Joon Lim <tgno3.com at gmail.com>
License: GPL-2
NeedsCompilation: no
Materials: NEWS
CRAN checks: DJL results

Documentation:

Reference manual: DJL.pdf

Downloads:

Package source: DJL_3.9.tar.gz
Windows binaries: r-devel: DJL_3.9.zip, r-release: DJL_3.9.zip, r-oldrel: DJL_3.9.zip
macOS binaries: r-release (arm64): DJL_3.9.tgz, r-oldrel (arm64): DJL_3.9.tgz, r-release (x86_64): DJL_3.9.tgz, r-oldrel (x86_64): DJL_3.9.tgz
Old sources: DJL archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=DJL to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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