accessors: Access or set information on cross-validation results

In aalfons/cvTools: Cross-validation tools for regression models

Description

Retrieve or set the names of cross-validation results, retrieve or set the identifiers of the models, or retrieve the number of cross-validation results or included models.

Usage

  cvNames(x)

  cvNames(x) <- value

  fits(x)

  fits(x) <- value

  ncv(x)

  nfits(x)

Arguments

x	an object inheriting from class "cv" or "cvSelect" that contains cross-validation results.
value	a vector of replacement values.

Value

cvNames returns the names of the cross-validation results. The replacement function thereby returns them invisibly.

fits returns the identifiers of the models for objects inheriting from class "cvSelect" and NULL for objects inheriting from class "cv". The replacement function thereby returns those values invisibly.

ncv returns the number of cross-validation results.

nfits returns the number of models included in objects inheriting from class "cvSelect" and NULL for objects inheriting from class "cv".

Author(s)

Andreas Alfons

See Also

cvFit, cvSelect, cvTuning

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

# "cv" object
ncv(cvFitLts50)
nfits(cvFitLts50)
cvNames(cvFitLts50)
cvNames(cvFitLts50) <- c("improved", "initial")
fits(cvFitLts50)
cvFitLts50

# "cvSelect" object
ncv(cvFitsLts)
nfits(cvFitsLts)
cvNames(cvFitsLts)
cvNames(cvFitsLts) <- c("improved", "initial")
fits(cvFitsLts)
fits(cvFitsLts) <- 1:2
cvFitsLts

aalfons/cvTools documentation built on May 10, 2019, 2:06 a.m.