MCP: helper function to implement MCP penalty The helper functions...
In plmmr: Penalized Linear Mixed Models for Correlated Data
MCP R Documentation
helper function to implement MCP penalty
The helper functions to implement each penalty.
Description
helper function to implement MCP penalty
The helper functions to implement each penalty.
Usage
MCP(z, l1, l2, gamma, v)
Arguments
z
a vector representing the solution over active set at each feature
l1
upper bound (on beta)
l2
lower bound (on beta)
gamma
The tuning parameter of the MCP penalty
v
the 'xtx' term
Value
numeric vector of the MCP-penalized coefficient estimates within the given bounds
plmmr documentation built on April 4, 2025, 12:19 a.m.
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| MCP | R Documentation |
helper function to implement MCP penalty The helper functions to implement each penalty.
Description
helper function to implement MCP penalty The helper functions to implement each penalty.
Usage
MCP(z, l1, l2, gamma, v)
Arguments
z |
a vector representing the solution over active set at each feature |
l1 |
upper bound (on beta) |
l2 |
lower bound (on beta) |
gamma |
The tuning parameter of the MCP penalty |
v |
the 'xtx' term |
Value
numeric vector of the MCP-penalized coefficient estimates within the given bounds
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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