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DJL  

Distance Measure Based Judgment and Learning
View on CRAN: Click here


Download and install DJL package within the R console
Install from CRAN:
install.packages("DJL")

Install from Github:
library("remotes")
install_github("cran/DJL")

Install by package version:
library("remotes")
install_version("DJL", "3.9")



Attach the package and use:
library("DJL")
Maintained by
Dong-Joon Lim
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-09-27
Latest Update: 2023-03-16
Description:
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.
How to cite:
Dong-Joon Lim (2015). DJL: Distance Measure Based Judgment and Learning. R package version 3.9, https://cran.r-project.org/web/packages/DJL. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.0 (2015-09-27 17:12), 1.5 (2015-10-01 11:13), 1.6 (2015-11-07 07:24), 1.7 (2015-11-17 14:40), 1.8 (2015-12-18 07:00), 1.9 (2016-01-17 10:59), 2.0 (2016-02-06 11:07), 2.1 (2016-03-24 23:39), 2.2 (2016-05-16 19:46), 2.3 (2016-06-06 07:48), 2.4 (2016-07-10 11:00), 2.5 (2016-08-18 10:02), 2.6 (2016-09-28 08:34), 2.7 (2018-04-17 17:21), 2.8 (2018-12-09 15:30), 2.9.1 (2019-02-11 15:03), 2.9.2 (2019-03-05 16:20), 2.9 (2019-02-05 06:43), 3.0 (2019-04-30 14:40), 3.1 (2019-11-16 18:10), 3.2 (2020-01-07 22:10), 3.3 (2020-04-29 17:40), 3.4 (2020-05-28 16:50), 3.5 (2020-09-12 18:40), 3.6 (2020-09-16 02:20), 3.7 (2021-05-20 17:00), 3.8 (2022-03-16 09:50)
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