fast.lasso.sum.ess.RdLasso calculation for summary statistics
fast.lasso.sum.ess(b.vec, s.vec, r2.mat, n, group, lambda, alpha, init.vec = NULL, max.iter = 100)
| b.vec | genetic effect estimates |
|---|---|
| s.vec | standard error of genetic effect estimates; |
| r2.mat | residual errors; |
| n | sample size; |
| group | 1-based group indicator |
| lambda | l1 penalty parameter |
| alpha | l2 penalty parameter |
| init.vec | inital guess |
| max.iter | maximum iteration |
a list: `beta` is the fitted regression coefficient vector, and `iteration` is the actual iteration.