cv.separate: cross-validation index function, separate train and test sets
In VARDetect: Multiple Change Point Detection in Structural VAR Models
View source: R/Functions_LpS.R
cv.separate R Documentation
cross-validation index function, separate train and test sets
Description
a function to setup training and testing datasets, select data point in test every nfold time points
Usage
cv.separate(period, nfold = 5)
Arguments
period
an input dataset with size of n by p
nfold
an positive integer, indicates the number of folds in cv
Value
a list object, includes
- train
training dataset
- test
test dataset
VARDetect documentation built on May 10, 2022, 9:07 a.m.
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View source: R/Functions_LpS.R
| cv.separate | R Documentation |
cross-validation index function, separate train and test sets
Description
a function to setup training and testing datasets, select data point in test every nfold time points
Usage
cv.separate(period, nfold = 5)
Arguments
period |
an input dataset with size of n by p |
nfold |
an positive integer, indicates the number of folds in cv |
Value
a list object, includes
- train
training dataset
- test
test dataset
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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