Description:	Collection of datasets from Sen & Srivastava:
Regression Analysis, Theory, Methods and Applications,
Springer.  Sources for individual data files are more fully
Packaged: Fri Sep 28 17:43:51 2007; halvorsen

Packaged: Mon Oct 15 09:42:41 2007; halvorsen

Packaged: Sat Oct 20 00:48:05 2007; halvorsen

Packaged: Sat Jan 26 21:42:42 2008; halvorsen

Description: Collection of datasets from Sen & Srivastava: Regression
Analysis, Theory, Methods and Applications, Springer.  Sources
for individual data files are more fully documented in the

Packaged: Thu Apr 22 20:43:08 2004; Kjetil

Packaged: Fri Sep 17 13:41:21 2004; halvorsen

Packaged: Thu Oct  6 17:47:38 2005; halvorsen

Packaged: Wed Feb  8 15:54:42 2006; halvorsen

Packaged: Sun Sep  3 16:20:58 2006; halvorsen

Author: Kjetil B Halvorsen <kjetil1001@gmail.com>
Description: Collection of datasets from Sen & Srivastava: "Regression
Analysis, Theory, Methods and Applications", Springer.  Sources

Title: Parsimonious Mixtures of MSEN and MTIN Distributions
Description: Implements parsimonious mixtures of MSEN and MTIN distributions via expectation-
maximization based algorithms for model-based clustering. For each mixture
component, parsimony is reached via the eigen-decomposition of the scale
matrices and by imposing a constraint on the tailedness parameter. This produces
a family of 28 parsimonious mixture models for each distribution.
Imports: doSNOW, foreach, snow, TSdist, tidyr, data.table, expint,

Title: Sensory and Consumer Data Mapping
Author: Ibtihel Rebhi [aut, cre], Rihab Boubakri [ctb], Dhafer Malouche [ctb]
Description: Obtain external preference map to explain consumer preferences in function of sensory
with options in dimension reduction methods and prediction models from linear and non linear regressions.
A smoothed version of the map is available and a comparison of maps stability from different features
before and after smoothing is provided which may help industrials to make good decisions about characteristics
A 'shiny' application is included. It presents an easy GUI for
the implemented functions as well as a comparative tool of fit models
performance using several criteria. Basic analysis such as characterization
of products, panelists and sessions likewise consumers segmentation are available.
Depends: R (>= 3.0.0), stats, grDevices, graphics
Imports: ggfortify, doBy, lattice, FactoMineR, MCMCpack, factoextra,
fields, ggdendro, glmulti, mgcv, plotly, shiny, ggplot2