sr3: SR3
In rohitchauhan5/SR3: A Unified Framework for Sparse Relaxed Regularized Regression
Description
SR3 Relaxed pursuit method for regularized least squares problems
of the form:
0.5*norm(A*x-b,2)^2 + lam*R(w) + 0.5*kap*norm(C*x-w,2)^2
over x and w. The output w represents a regularized solution of
the least squares problem described by A and b.
Usage
1
Arguments
A
double precision real or complex matrix (dimension, say, MxN)
b
double precision real or complex vector (length M)
...
Optional arguments
rohitchauhan5/SR3 documentation built on May 31, 2019, 5:42 a.m.
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Description
SR3 Relaxed pursuit method for regularized least squares problems
of the form:
0.5*norm(A*x-b,2)^2 + lam*R(w) + 0.5*kap*norm(C*x-w,2)^2
over x and w. The output w represents a regularized solution of
the least squares problem described by A and b.
Usage
1 |
Arguments
A |
double precision real or complex matrix (dimension, say, MxN) |
b |
double precision real or complex vector (length M) |
... |
Optional arguments |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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