Last data update: 2014.03.03
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R: Subsetting cross-validation results
Subsetting cross-validation results
Description
Extract subsets of results from (repeated) K-fold
cross-validation.
Usage
## S3 method for class 'cv'
subset(x, select = NULL, ...)
## S3 method for class 'cvSelect'
subset(x, subset = NULL,
select = NULL, ...)
Arguments
x |
an object inheriting from class "cv" or
"cvSelect" that contains cross-validation
results.
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subset |
a character, integer or logical vector
indicating the subset of models for which to keep the
cross-validation results.
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select |
a character, integer or logical vector
indicating the columns of cross-validation results to be
extracted.
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... |
currently ignored.
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Value
An object similar to x containing just the
selected results.
Author(s)
Andreas Alfons
See Also
cvFit , cvSelect ,
cvTuning , subset
Examples
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
# extract reweighted LTS results with 50% subsets
subset(cvFitLts50, select = "reweighted")
subset(cvFitsLts, subset = c(TRUE, FALSE), select = "reweighted")
Results
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