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FLLat
View on CRAN: Click
here
Download and install FLLat package within the R console
Install from CRAN:
install.packages("FLLat")
Install from Github:
library("remotes")
install_github("cran/FLLat") Install by package version:
library("remotes")
install_version("FLLat", "1.2-1") Attach the package and use:
library("FLLat")
Maintained by
Gen Nowak
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2011-06-05
Latest Update:
Description:
Fits the Fused Lasso Latent Feature model, which is used for modeling multi-sample aCGH data to identify regions of copy number variation (CNV). Produces a set of features that describe the patterns of CNV and a set of weights that describe the composition of each sample. Also provides functions for choosing the optimal tuning parameters and the appropriate number of features, and for estimating the false discovery rate.
How to cite:
Gen Nowak (2011). FLLat: Fused Lasso Latent Feature Model. R package version 1.2-1, https://cran.r-project.org/web/packages/FLLat. Accessed 06 Jun. 2026.
Previous versions and publish date:
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Other R packages that FLLat depends,
imports, suggests or enhances
Complete documentation for FLLat
Functions, R codes and Examples using
the FLLat R package
Some associated functions: FLLat.BIC . FLLat.FDR . FLLat.PVE . FLLat . plot.FLLat . predict.FLLat . simaCGH .
Some associated R codes: CheckPars.R . FLLat.BIC.R . FLLat.FDR.R . FLLat.PVE.R . FLLat.R . Max.Lam0.R . plot.FDR.R . plot.FLLat.R . plot.PVE.R . predict.FLLat.R . Full FLLat package functions and examples
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