Authors@R: c(person("Rui", "Ren", role=c("aut", "cre"),
Imports: MFPCA, cluster, fpc, fda, fda.usc, funData, stats, graphics

person(given = "Solar Durability and Lifetime Extension Center",
Description: We provide here tools used by the Solar Durability and Lifetime Extension Center (SDLE)
for FAIRifying data from materials science projects. Functions have been created for numerous tools common
in the field in order to make the metadata more Findable, Accessible, Interoperable, and Reproducible.
Author: Will Oltjen [aut, cre] (<https://orcid.org/0000-0003-0380-1033>),
Solar Durability and Lifetime Extension Center [cph, fnd]

Title: A Convex Formulation for Modeling Interactions with Strong
Description: Fits penalized linear and logistic regression models with pairwise interaction terms.

Package: FAMT
Type: Package
Title: Factor Analysis for Multiple Testing (FAMT) : simultaneous tests
under dependence in high-dimensional data
Version: 2.0
Date: 2010-05-03
Author: David Causeur, Chloe Friguet, Magalie Houee-Bigot, Maela
Kloareg
Maintainer: David Causeur <David.Causeur@agrocampus-ouest.fr>
Description: The method proposed in this package takes into account the
impact of dependence on the multiple testing procedures for
high-throughput data as proposed by Friguet et al. (2009). The
common information shared by all the variables is modeled by a
factor analysis structure. The number of factors considered in
the model is chosen to reduce the false discoveries variance in
multiple tests. The model parameters are estimated thanks to an
EM algorithm. Adjusted tests statistics are derived, as well as
the associated p-values. The proportion of true null hypotheses
(an important parameter when controlling the false discovery
rate) is also estimated from the FAMT model. Graphics are
proposed to interpret and describe the factors.
Depends: mnormt
License: GPL (>= 2)
URL: http://famt.free.fr/
LazyLoad: yes
Packaged: 2010-05-11 18:48:00 UTC; Kloareg
Repository: CRAN
Date/Publication: 2010-05-12 07:21:49

Package: FAMT
Type: Package
Title: Factor Analysis for Multiple Testing (FAMT) : simultaneous tests
under dependence in high-dimensional data
Version: 2.1
Date: 2010-05-03
Author: David Causeur, Chloe Friguet, Magalie Houee-Bigot, Maela
Kloareg
Maintainer: David Causeur <David.Causeur@agrocampus-ouest.fr>
Description: The method proposed in this package takes into account the
impact of dependence on the multiple testing procedures for
high-throughput data as proposed by Friguet et al. (2009). The
common information shared by all the variables is modeled by a
factor analysis structure. The number of factors considered in
the model is chosen to reduce the false discoveries variance in
multiple tests. The model parameters are estimated thanks to an
EM algorithm. Adjusted tests statistics are derived, as well as
the associated p-values. The proportion of true null hypotheses
(an important parameter when controlling the false discovery
rate) is also estimated from the FAMT model. Graphics are
proposed to interpret and describe the factors.
Depends: mnormt, impute
License: GPL (>= 2)
URL: http://famt.free.fr/
LazyLoad: yes
Packaged: 2010-07-08 15:11:47 UTC; HOUEE
Repository: CRAN
Date/Publication: 2010-07-24 19:41:03