numNoiseCoeff: Variable selection using shrinkage priors :: numNoiseCoeff
In VsusP: Variable Selection using Shrinkage Priors
View source: R/Sequential2Means.R
numNoiseCoeff R Documentation
Variable selection using shrinkage priors :: numNoiseCoeff
Description
Variable selection using shrinkage priors :: numNoiseCoeff
Usage
numNoiseCoeff(Beta.i, b.i_r)
Arguments
Beta.i
N by p matrix consisting of N posterior samples of p variables
b.i_r
tuning parameter value from Sequential 2-means (S2M) variable selection algorithm.
Value
number of noise coefficients of numeric data type
VsusP documentation built on June 25, 2024, 5:07 p.m.
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View source: R/Sequential2Means.R
| numNoiseCoeff | R Documentation |
Variable selection using shrinkage priors :: numNoiseCoeff
Description
Variable selection using shrinkage priors :: numNoiseCoeff
Usage
numNoiseCoeff(Beta.i, b.i_r)
Arguments
Beta.i |
N by p matrix consisting of N posterior samples of p variables |
b.i_r |
tuning parameter value from Sequential 2-means (S2M) variable selection algorithm. |
Value
number of noise coefficients of numeric data type
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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