Package: cops
Title: Cluster Optimized Proximity Scaling
Version: 1.0-2
Date: 2019-10-28
Authors@R: c(person(given="Thomas", family="Rusch", email="thomas.rusch@wu.ac.at", role = c("aut","cre"), comment = c(ORCID = "0000-0002-7773-2096")), person(given="Jan",family="de Leeuw", role = c("aut")), person(given="Patrick",family="Mair", role = "aut"))
Maintainer: Thomas Rusch <thomas.rusch@wu.ac.at>
Description: Cluster optimized proximity scaling (COPS) refers to multidimensional scaling (MDS) methods that aim at pronouncing the clustered appearance of the configuration. They achieve this by transforming proximities/distances with power functions and augment the fitting criterion with a clusteredness index, the OPTICS Cordillera (Rusch, Hornik & Mair, 2018, <doi:10.1080/10618600.2017.1349664>). There are two variants: One for finding the configuration directly for given parameters (COPS-C) for ratio, interval and non-metric MDS (Borg & Groenen, 2005, ISBN:978-0-387-28981-6), and one for using the augmented fitting criterion to find optimal parameters (P-COPS). The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying different MDS models in a COPS framework like ratio, interval and non-metric MDS for COPS-C and P-COPS with Torgerson scaling (Torgerson, 1958, ISBN:978-0471879459), scaling by majorizing a complex function (SMACOF; de Leeuw, 1977, <https://escholarship.org/uc/item/4ps3b5mj>), Sammon mapping (Sammon, 1969, <doi:10.1109/T-C.1969.222678>), elastic scaling (McGee, 1966, <doi:10.1111/j.2044-8317.1966.tb00367.x>), s-stress (Takane, Young & de Leeuw, 1977, <doi:10.1007/BF02293745>, r-stress (de Leeuw, Groenen & Mair, 2016, <https://rpubs.com/deleeuw/142619>), power-stress (Buja & Swayne, 2002 <doi:10.1007/s00357-001-0031-0>) and power elastic scaling, power Sammon mapping and approximated power stress (Rusch, Mair & Hornik, 2015, <https://bach-s59.wu.ac.at/4888/>). All of these models can also solely be fit as MDS with power transformations. The package further contains a function for pattern search optimization, the "Adaptive Luus-Jakola Algorithm" (Rusch, Mair & Hornik, 2015, <https://bach-s59.wu.ac.at/4888/>).
Depends: R (>= 3.1.2), cordillera (>= 0.7-2), smacof (>= 1.10-4)
Imports: MASS, minqa, pso, scatterplot3d, NlcOptim, Rsolnp, dfoptim,
        subplex, cmaes, crs, nloptr, rgl, rgenoud, GenSA
Enhances: stats
Suggests: testthat
License: GPL-2 | GPL-3
LazyData: true
URL: http://r-forge.r-project.org/projects/stops/
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-10-28 22:48:38 UTC; trusch
Author: Thomas Rusch [aut, cre] (<https://orcid.org/0000-0002-7773-2096>),
  Jan de Leeuw [aut],
  Patrick Mair [aut]
Repository: CRAN
Date/Publication: 2019-11-01 09:30:02 UTC
