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:

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