Authors@R: person("Louis","Capitaine", email = "louis.capitaine@u-bordeaux.fr", role = c("aut", "cre"))
Description: Random forests are a statistical learning method widely used in many areas of scientific research essentially for its ability to learn complex relationships between input and output variables and also its capacity to handle high-dimensional data. However, current random forests approaches are not flexible enough to handle longitudinal data, shapes and images.  In this package, we introduce Fréchet trees and Fréchet random forests, which allow to manage data for which input and output can either curves, scalars, factors, shapes or images. To this end, a new way of splitting the nodes of trees is introduced and the prediction procedures of trees and forests are generalized.
Imports: stats, kmlShape, foreach, doParallel, graphics, stringr,
salso, RiemBase, geomorph, Evomorph, DescTools, parallel,
Packaged: 2020-06-18 09:33:58 UTC; capitainelouis

Description: The package FreeSortR provides tools for describing and analysing free sorting data. Main methods are computation of consensus partition and factorial analysis of the dissimilarity matrix between stimuli (using multidimensional scaling approach).
Depends: methods, smacof, vegan, ellipse

Depends: R (>= 3.1), methods, smacof, vegan, ellipse

Description: Provides tools for describing and analysing free sorting data. Main methods are computation of consensus partition and factorial analysis of the dissimilarity matrix between stimuli (using multidimensional scaling approach).
Packaged: 2016-05-24 14:40:51 UTC; Philippe-Courcoux

Packaged: 2017-12-15 19:47:43 UTC; Philippe-Courcoux

person(c("Ronald", "E."), "Robertson",, "rrobertson@aibrt.org", c("cre", "aut")),
person("AIBRT", email = "info@aibrt.org", role = "cph")
Title: Frequency Profiles Computing and Plotting
Description: Tools for generating an informative type of line graph, the frequency profile,
which allows single behaviors, multiple behaviors, or the specific behavioral patterns
of individual subjects to be graphed from occurrence/nonoccurrence behavioral data.
Maintainer: Ronald E. Robertson <rrobertson@aibrt.org>