Description Usage Arguments Value Author(s) See Also Examples
Produce a summary of results from (repeated) K-fold cross-validation.
1 2 3 4 5 6 7 8 |
object |
an object inheriting from class |
... |
currently ignored. |
An object of class "summary.cv"
,
"summary.cvSelect"
or "summary.cvTuning"
,
depending on the class of object
.
Andreas Alfons
cvFit
, cvSelect
,
cvTuning
, summary
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | library("robustbase")
data("coleman")
set.seed(1234) # set seed for reproducibility
## set up folds for cross-validation
folds <- cvFolds(nrow(coleman), K = 5, R = 10)
## compare raw and reweighted LTS estimators for
## 50% and 75% subsets
# 50% subsets
fitLts50 <- ltsReg(Y ~ ., data = coleman, alpha = 0.5)
cvFitLts50 <- cvLts(fitLts50, cost = rtmspe, folds = folds,
fit = "both", trim = 0.1)
# 75% subsets
fitLts75 <- ltsReg(Y ~ ., data = coleman, alpha = 0.75)
cvFitLts75 <- cvLts(fitLts75, cost = rtmspe, folds = folds,
fit = "both", trim = 0.1)
# combine results into one object
cvFitsLts <- cvSelect("0.5" = cvFitLts50, "0.75" = cvFitLts75)
cvFitsLts
# summary of the results with the 50% subsets
summary(cvFitLts50)
# summary of the combined results
summary(cvFitsLts)
|
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