R: Distance Measure Based Judgment and Learning

# Distance Measure Based Judgment and Learning

## Documentation for package ‘DJL’ version 3.9

- DESCRIPTION file.
- Package NEWS.

## Help Pages

dataset.airplane.2017 | Dataset of commercial airplanes from 1965 to 2017.
dataset.engine.2015 | Dataset of auto engines from MY2005 to MY2015.
dataset.hev.2013 | Dataset of hybrid electric vehicles from MY1997 to MY2013.
dm.ddf | Distance measure using DDF
dm.dea | Distance measure using DEA
dm.dynamic.bc | Dynamic DEA in the presence of intertemporal Budget Constraints
dm.hdf | Distance measure using HDF
dm.mahalanobis | Distance measure using Mahalanobis distance for outlier detection
dm.network.dea | Distance measure using DEA on a two-stage network structure
dm.sbm | Distance measure using SBM
dm.sf | Distance measure using SF
ma.aps.reg | Combinatorial search (all possible subset) for regression analysis
map.corr | Correlation mapping for reliability test
map.soa.ddf | SOA mapping using DDF
map.soa.dea | SOA mapping using DEA
map.soa.hdf | SOA mapping using HDF
map.soa.sbm | SOA mapping using SBM
map.soa.sf | SOA mapping using SF
plp | Print LP object
roc.dea | Rate of change (RoC) calculation using DEA
roc.hdf | Rate of change (RoC) calculation using HDF
roc.malmquist | Malmquist Index: time-series productivity analysis
roc.sf | Rate of change (RoC) calculation using SF
target.arrival.dea | Arrival target setting using DEA
target.arrival.hdf | Arrival target setting using HDF
target.arrival.sf | Arrival target setting using SF
target.spec.dea | Spec target setting using DEA