Implementation of the Conic Multivariate Adaptive Regression
Splines in R
c(person("Fatma", "Yerlikaya-Ozkurt", email = "fatma.yerlikaya@atilim.edu.tr", role = "aut"),
person("Ceyda", "Yazici", email = "ceydayazici86@gmail.com", role = c("aut", "cre")),
person("Inci", "Batmaz", email = "ibatmaz@metu.edu.tr", role = c("aut")))
Fatma Yerlikaya-Ozkurt [aut],
Ceyda Yazici [aut, cre],
Inci Batmaz [aut]
MOSEK (http://www.mosek.com) and MOSEK License for
use of Rmosek
An implementation of 'Conic Multivariate Adaptive Regression Splines (CMARS)' in R.
See Weber et al. (2011) CMARS: a new contribution to nonparametric regression with
multivariate adaptive regression splines supported by continuous optimization,
<DOI:10.1080/17415977.2011.624770>. It constructs models by using the terms
obtained from the forward step of MARS and then estimates parameters by using
'Tikhonov' regularization and conic quadratic optimization. It is possible to
construct models for prediction and binary classification. It provides performance
measures for the model developed. The package needs the optimisation software 'MOSEK'
<https://www.mosek.com/> to construct the models. Please follow the instructions in
'Rmosek' for the installation.
earth, graphics, Rmosek, stats, stringr, utils, Matrix, AUC,
Ryacas0

earth, graphics, Rmosek, stats, stringr, utils, Matrix, AUC,
Ryacas0, ROCR

Covariance Matrix Adapting Evolutionary Strategy
Single objective optimization using a CMA-ES.
Heike Trautmann <trautmann@statistik.tu-dortmund.de> and Olaf
Mersmann <olafm@statistik.tu-dortmund.de> and David Arnu
<david.arnu@statistik.tu-dortmund.de>

Covariance Matrix Adaptation Evolution Strategy
Pure R implementation of the Covariance Matrix Adaptation -
Evolution Strategy (CMA-ES) with optional restarts (IPOP-CMA-ES).
c(person("Jakob", "Bossek", email = "j.bossek@gmail.com", role =
c("aut", "cre")))
ParamHelpers (>= 1.3), BBmisc (>= 1.6), checkmate (>= 1.1),
smoof (>= 1.1)

ParamHelpers (>= 1.8), BBmisc (>= 1.6), checkmate (>= 1.1),
smoof (>= 1.4)