Conventional and Fuzzy Data Envelopment Analysis
Vicente Coll-Serrano, Vicente Bolos, Rafael Benitez Suarez <rabesua@uv.es>
Set of functions for Data Envelopment Analysis. It runs both classic and fuzzy DEA models. See: Banker, R.; Charnes, A.; Cooper, W.W. (1984). <doi:10.1287/mnsc.30.9.1078>, Charnes, A.; Cooper, W.W.; Rhodes, E. (1978). <doi:10.1016/0377-2217(78)90138-8> and Charnes, A.; Cooper, W.W.; Rhodes, E. (1981). <doi: 10.1287/mnsc.27.6.668>.
lpSolve, ggplot2, tidyr, plotly, igraph, writexl, dplyr,
methods, gridExtra

Set of functions for Data Envelopment Analysis. It runs both classic and fuzzy DEA models.See: Banker, R.; Charnes, A.; Cooper, W.W. (1984). <doi:10.1287/mnsc.30.9.1078>, Charnes, A.; Cooper, W.W.; Rhodes, E. (1978). <doi:10.1016/0377-2217(78)90138-8> and Charnes, A.; Cooper, W.W.; Rhodes, E. (1981). <doi:10.1287/mnsc.27.6.668>.

lpSolve, ggplot2, tidyr, plotly, igraph, writexl, dplyr,
methods, gridExtra, grDevices

Statistical deadband algorithms are based on the Send-On-Delta concept as in Miskowicz(2006,<doi:10.3390/s6010049>). A collection of functions compare effectiveness and fidelity of sampled signals using statistical deadband algorithms.

Learning Bayesian Networks with Mixed Variables
Susanne Gammelgaard Bøttcher <alma@math.auc.dk>, Claus Dethlefsen <dethlef@math.auc.dk>.
Bayesian networks with continuous and/or discrete variables can be learned and compared from data.

Susanne Gammelgaard Bøttcher <alma@math.aau.dk>, Claus Dethlefsen <dethlef@math.aau.dk>.

addarrows.R autosearch.R conditional.R cycletest.R drawnetwork.R findex.R generic.R genlatex.R heuristic.R inspectprob.R jointcont.R jointdisc.R jointprior.R learning.R makesimprob.R maketrylist.R master.R network.R networkfamily.R node.R numbermixed.R perturb.R postc.R postc0.R postdist.R readnet.R rnetwork.R savenet.R unique.R anetworkclass.R dealObjects.R usermenus.R

Susanne Gammelgaard Bøttcher <alma@math.aau.dk>, Claus Dethlefsen <aas.claus.dethlefsen@nja.dk>.

addarrows.R autosearch.R conditional.R cycletest.R drawnetwork.R findex.R generic.R genlatex.R heuristic.R inspectprob.R jointcont.R jointdisc.R jointprior.R learning.R makesimprob.R fullsimprob.R maketrylist.R master.R network.R networkfamily.R node.R numbermixed.R perturb.R postc.R postc0.R postdist.R readnet.R rnetwork.R savenet.R unique.R anetworkclass.R dealObjects.R usermenus.R