Description Usage Arguments Value Author(s) Examples
Applies a cross-validation of DS results, using the same strategy as in the DS exercise. Any step-wise screening is applied for each iteration independently of that used to identify the subset of skillful predictors in the original analysis. The model coeffiecients (beta) is saved for each iteration, and both correlation and root-mean-squared-error are returned as scores.
1 2 3 | crossval(x, m=5, ...)
crossval.ds(x, m=5, ...)
crossval.list(x, m=5, ...)
|
x |
The results from |
m |
window with - leave m-out for each iteration. |
Cross-validation object.
R.E. Benestad
1 2 3 4 5 6 7 |
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