Title: Multivariate analysis for a mixture of quantitative and
Author: Marie Chavent and Vanessa Kuentz and Amaury Labenne and Benoit Liquet and Jerome Saracco
Description: Principal Component Analysis, orthogonal rotation and multiple factor
analysis for a mixture of quantitative and qualitative variables.
Collate: 'PCAmix.R' 'PCArot.R' 'plot.PCAmix.R' 'predict.PCAmix.R'
'Lg.pond.R' 'Lg.R' 'RV.R' 'RV.pond.R' 'MFAmix.R'
Packaged: 2014-02-03 10:26:19 UTC; Amaury.Labenne

'nb.level.R' 'Tri.Data.R' 'Lg.pond.R' 'Lg.R' 'RV.R' 'RV.pond.R'
Packaged: 2014-02-10 11:04:58 UTC; Amaury.Labenne

Title: Multivariate Analysis of Mixed Data
Author: Marie Chavent and Vanessa Kuentz and Amaury Labenne and Benoit Liquet and Jerome Saracco.
Description: Principal Component Analysis, orthogonal rotation and multiple factor analysis for a mixture of quantitative and qualitative variables.
Packaged: 2014-12-05 10:38:10 UTC; Amaury.Labenne

Description: Principal Component Analysis, orthogonal rotation and multiple
factor analysis for a mixture of quantitative and qualitative variables.

Description: Implements principal component analysis, orthogonal rotation and multiple

Title: Semiparametric regression analysis of panel count data using
Author: Bin Yao <yaob@email.sc.edu> and Lianming Wang <wangl@stat.sc.edu>
Description: Semiparametric regression analysis of panel count data under the non-homogeneous Poisson
process model with and without Gamma frailty using monotone splines.
Imports: nleqslv (>= 2.2), matrixcalc (>= 1.0-3)

Title: Finding the Number of Significant Principal Components
Description: Implements methods to automate the Auer-Gervini graphical
Bayesian approach for determining the number of significant
principal components. Automation uses clustering, change points, or
simple statistical models to distinguish "long" from "short" steps
in a graph showing the posterior number of components as a function
of a prior parameter. See <doi:10.1101/237883>.
Imports: methods, stats, graphics, oompaBase, kernlab, changepoint, cpm