Description Usage Arguments Value References See Also Examples
Computes K-Fold cross validation based on mean squared prediction error.
1 | cv.ES(x,object,K=10,M)
|
x |
Data Matrix. The columns represent the different variables, while the rows represent identically and independently distributed samples. |
object |
Lars object, generated from ES function. |
K |
Number of Folds in cross validation. |
M |
A vector of values that determine the points where cross validation are done. If not specified, the value of M will be determined using the object |
cv.ES
picks a model which minimizes the mean squared prediction errors using the input vector M. cv.ES
also pick a model with a mean squared prediction error less than or equals to the minimum mean square prediction plus its standard error.
Edge Selection for Undirected Graphs
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