| prox_sorted_L1 | R Documentation |
Compute the prox for the sorted L1 norm. That is, given a vector x
and a decreasing vector \lambda, compute the unique value of y
minimizing
\frac{1}{2} \Vert x - y \Vert_2^2 +
\sum_{i=1}^n \lambda_i |x|_{(i)}.
At present, two methods for computing the sorted L1 prox are
supported. By default, we use a fast custom C implementation. Since SLOPE
can be viewed as an isotonic regression problem, the prox can also be
computed using the isotone package. This option is provided
primarily for testing.
prox_sorted_L1(x, lambda, method = c("c", "isotone"))
x |
input vector |
lambda |
vector of |
method |
underlying prox implementation, either 'c' or 'isotone' (see Details) |
This function has been adapted (with only cosmetic changes) from
the R package SLOPE version 0.1.3, due to this function being
deprecated and defunct in SLOPE versions which are newer than 0.1.3.
The solution vector y.
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