Packaged: 2018-03-21 12:27:48 UTC; Paolo Giordani

Description: Algorithms for fuzzy clustering, cluster validity indices and plots for cluster validity and visualizing fuzzy clustering results

Author: Paolo Giordani, Maria Brigida Ferraro, Alessio Serafini
Depends: R (>= 3.3), base, stats, graphics, grDevices, utils
Packaged: 2018-10-19 10:21:13 UTC; alessioserafini

Imports: Rcpp (>= 0.12.5), MASS (>= 7.3), cluster
Packaged: 2018-10-15 14:22:40 UTC; alessioserafini

Packaged: 2019-09-16 09:37:03 UTC; alessioserafini

Packaged: 2019-05-14 13:31:36 UTC; alessioserafini

Title: Inference of Fuzzy Cognitive Maps (FCMs)
Author: Zoumpoulia Dikopoulou <dikopoulia@gmail.com> <zoumpolia.dikopoulou@uhasselt.be>, Elpiniki Papageorgiou <epapageorgiou@teiste.gr>, <e.i.papageorgiou75@gmail.com>
Description: Provides a selection of 6 different inference rules and 4 threshold functions in order to obtain the inference of the FCM (Fuzzy Cognitive Map). Moreover, the 'fcm' package returns a data frame of the concepts' values of each state after the inference procedure. Fuzzy cognitive maps were introduced by Kosko (1986) <doi:10.1002/int.4550010405> providing ideal causal cognition tools for modeling and simulating dynamic systems.

Description: Provides a selection of 3 different inference rules (including additionally the clamped types of the referred inference rules) and 4 threshold functions in order to obtain the inference of the FCM (Fuzzy Cognitive Map). Moreover, the 'fcm' package returns a data frame of the concepts' values of each state after the inference procedure. Fuzzy cognitive maps were introduced by Kosko (1986) <doi:10.1002/int.4550010405> providing ideal causal cognition tools for modeling and simulating dynamic systems.

Title: Functional Concurrent Regression for Sparse Data
Description: Dynamic prediction in functional concurrent regression with an application to child growth. Extends the pffr() function from the 'refund' package to handle the scenario where the functional response and concurrently measured functional predictor are irregularly measured.  Leroux et al. (2017), Statistics in Medicine, <doi:10.1002/sim.7582>.
Packaged: 2018-03-11 17:38:36 UTC; andrewleroux