DJL: Distance Measure Based Judgment and Learning

Implements various decision support tools related to the new product development. 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, risk analysis, technology adoption model, new product target setting, etc.

Install the latest version of this package by entering the following in R:
AuthorDong-Joon Lim, PhD
Date of publication2016-09-28 08:34:03
MaintainerDong-Joon Lim <>

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dataset.airplane.2017 Man page
dataset.engine.2015 Man page
dataset.hev.2013 Man page
dm.ddf Man page
dm.dea Man page
dm.hdf Man page
dm.mahalanobis Man page
dm.sbm Man page
dm.sf Man page
ma.aps.reg Man page
map.corr Man page
map.soa.ddf Man page
map.soa.dea Man page
map.soa.hdf Man page
map.soa.sbm Man page
map.soa.sf Man page
roc.dea Man page
roc.hdf Man page
roc.sf Man page
target.arrival.dea Man page
target.arrival.hdf Man page
target.arrival.sf Man page
target.spec.dea Man page

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