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FAMT
View on CRAN: Click
here
Download and install FAMT package within the R console
Install from CRAN:
install.packages("FAMT")
Install from Github:
library("remotes")
install_github("cran/FAMT")
Install by package version:
library("remotes")
install_version("FAMT", "2.6")
Attach the package and use:
library("FAMT")
Maintained by
David Causeur
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2010-05-12
Latest Update: 2022-05-09
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.
How to cite:
David Causeur (2010). FAMT: Factor Analysis for Multiple Testing (FAMT) : Simultaneous Tests under Dependence in High-Dimensional Data. R package version 2.6, https://cran.r-project.org/web/packages/FAMT. Accessed 06 May. 2025.
Previous versions and publish date:
Other packages that cited FAMT R package
View FAMT citation profile
Other R packages that FAMT depends,
imports, suggests or enhances
Complete documentation for FAMT
Functions, R codes and Examples using
the FAMT R package
Some associated functions: FAMT-package . annotations . as.FAMTdata . covariates . defacto . emfa . expression . modelFAMT . nbfactors . pi0FAMT . raw.pvalues . residualsFAMT . summaryFAMT .
Some associated R codes: FAMT_2.5-internal.R . as.FAMTdata.R . defacto.R . emfa.R . modelFAMT.R . nbfactors.R . pi0FAMT.R . raw.pvalues.R . residualsFAMT.R . summaryFAMT.R . Full FAMT package functions and examples
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