QBIC: High-dimensional BIC.
In penplaqr/penplaqr:
Description
QBIC computes the high-dimensional BIC described in Sherwood and Wang (2016).
Usage
1
QBIC(tau, resids, p_linear, degfree)
Arguments
resids
a vector of residuals from the candidate model.
p_linear
the number of candidate linear covariates.
lambda
a nonnegative scalar; the tuning parameter.
degree
the degrees of freedom of the candidate model.
penplaqr/penplaqr documentation built on May 6, 2019, 11:44 a.m.
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Description
QBIC computes the high-dimensional BIC described in Sherwood and Wang (2016).
Usage
1 | QBIC(tau, resids, p_linear, degfree)
|
Arguments
resids |
a vector of residuals from the candidate model. |
p_linear |
the number of candidate linear covariates. |
lambda |
a nonnegative scalar; the tuning parameter. |
degree |
the degrees of freedom of the candidate model. |
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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