Files in xueweic/APGD
TGPred: Efficient methods for predicting target genes of a transcription factor by integrating statistics, machine learning, and optimization.
DESCRIPTION
NAMESPACE
R/CalculateAdj.R
R/CalculateLaplacian.R
R/ConstructNetwork.R
R/GraphicalModel.R
R/HuberENET_Beta.R
R/HuberENET_SP.R
R/HuberLasso_Beta.R
R/HuberLasso_SP.R
R/HuberNet_Beta.R
R/HuberNet_SP.R
R/Lambda_gird.R
R/MSEENET_Beta.R
R/MSEENET_SP.R
R/MSELasso_Beta.R
R/MSELasso_SP.R
R/MSENet_Beta.R
R/MSENet_SP.R
R/Sample_data.R
R/SimulationData.R
R/SupportFunctions.R
README.md
TGPred.Rproj
data/Sample_data.rda
man/CalculateAdj.Rd
man/CalculateLaplacian.Rd
man/ConstructNetwork.Rd
man/GraphicalModel.Rd
man/HuberENET_Beta.Rd
man/HuberENET_SP.Rd
man/HuberFunction.Rd
man/HuberLasso_Beta.Rd
man/HuberLasso_SP.Rd
man/HuberNet_Beta.Rd
man/HuberNet_SP.Rd
man/Huber_grid.Rd
man/Lambda_gird.Rd
man/MSEENET_Beta.Rd
man/MSEENET_SP.Rd
man/MSELasso_Beta.Rd
man/MSELasso_SP.Rd
man/MSENet_Beta.Rd
man/MSENet_SP.Rd
man/Sample_data.Rd
man/SimulationData.Rd
man/figures/Beta_hat_APGD.jpeg
man/figures/Beta_hat_CVX.jpeg
man/figures/README-pressure-1.png
