Joint Feature Screening via Sparse MLE
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R softeware and R package glmnet
# Install package from CRAN:
install.packages("SMLE")
set.seed(1)
Data_sim <- Gen_Data(n = 200, p = 1000, correlation = "AR", rho = 0.9, sigma = 1,
family = "gaussian", pos_truecoef = c(1,3,5,7,9),
effect_truecoef = (0.8)*c(2,-3,-3,2,-4))
fit_path <- SMLE(Y = Data_sim$Y, X = Data_sim$X , k = 10 , coef_initial = rep(0,1000))
plot(fit_path)
For more examples, please refer to the Vignette
Distributed under the GPL-3 License.
Qianxiang Zang - qzang023@uottawa.ca
