tuning_cv_svd: Weighted leave-one-out crossvalidation error
In khellton/influridge: Visualize Influence of Observations in Ridge Regression
tuning_cv_svd R Documentation
Weighted leave-one-out crossvalidation error
Description
This function produces the leave-one-out squared cross-validation error for a given tuning parameter and weight.
Usage
tuning_cv_svd(lambda, w, svd.int, y.int)
Arguments
lambda
scalar, ridge tuning parameter.
w
vector of length n, weigths for all observations.
svd.int
svd object, singular value decomposition of the input matrix.
y.int
numerical output vector; response variable.
khellton/influridge documentation built on Dec. 23, 2024, 9:24 a.m.
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| tuning_cv_svd | R Documentation |
Weighted leave-one-out crossvalidation error
Description
This function produces the leave-one-out squared cross-validation error for a given tuning parameter and weight.
Usage
tuning_cv_svd(lambda, w, svd.int, y.int)
Arguments
lambda |
scalar, ridge tuning parameter. |
w |
vector of length n, weigths for all observations. |
svd.int |
svd object, singular value decomposition of the input matrix. |
y.int |
numerical output vector; response variable. |
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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