subset.cv {cvTools}

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.

select

a character, integer or logical vector indicating the columns of cross-validation results to be extracted.

...

currently ignored.

subset

a character, integer or logical vector indicating the subset of models for which to keep the cross-validation results.

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")