imp.lasso: Lower and upper estimates of LASSO coefficients
In tathagatabasu/bootlasso: Boot-strap Method for LASSO

Lower and upper estimates of LASSO coefficients using optimization over weights

1 2	imp.lasso(lambda, x, y, wtl, wtu, ts = NULL, method = lasso_optim_cd, n_it = 10)

`lambda`	value of the penalty parameter
`x`	predictors
`y`	response
`wtl`	lower bound of the weights for the coefficients of weighted LASSO
`wtu`	upper bound of the weights for the coefficients of weighted LASSO
`ts`	stepsize for proximal gradient and sub-gradient method (use opt_ts() to generate stepsize). Defaults to NULL
`method`	lasso optimization function. Three different methods are available to use. method = c(lasso_optim_cd, lasso_optim_sg, lasso_optim_pg). Defaults to lasso_optim_cd
`n_it`	number of iteration for lasso_optim_cd method. Default value is 10.