logit_cda_r: Optimize a logistic regression model by coordinate descent...
In iilasso: Independently Interpretable Lasso

Optimize a logistic regression model by coordinate descent algorithm using a design matrix with R

1 2	logit_cda_r(X_tilde, y, lambda, R, init.beta, delta, maxit, eps, warm, strong, sparse)

`X_tilde`	standardized matrix of explanatory variables
`y`	vector of objective variable
`lambda`	lambda sequence
`R`	matrix using exclusive penalty term
`init.beta`	initial values of beta
`delta`	ratio of regularization between l1 and exclusive penalty terms
`maxit`	max iteration
`eps`	convergence threshold for optimization
`warm`	warm start direction: "lambda" (default) or "delta"
`strong`	whether use strong screening or not
`sparse`	whether use sparse matrix or not