crossval: Cross-validation of palaeoecological transfer function models

Description

Performs leave-one-out, k-fold, n k-fold and bootstrap cross-validation of palaeoecological transfer function models.

Usage

crossval(obj, ...)
# S3 method for wa
crossval(obj, method = c("LOO","kfold","bootstrap"),
         nboot = 100, nfold = 10, folds = 5,
         verbose = getOption("verbose"), ...)
# S3 method for pcr
crossval(obj, method = c("LOO","kfold","bootstrap"),
         ncomp, nboot = 100, nfold = 10, folds = 5,
         verbose = getOption("verbose"), ...)

Value

Returns an object of class "crossval", a list with the following components:

fitted.values: numeric vector; the cross-validated estimates of the response.
residuals: numeric vector; residuals computed from the cross-validated estimates of the response.
performance: data frame; cross-validation performance statistics for the model.
CVparams: list; parameters holding details of the cross-validation process.
call: the matched call.

Arguments

obj: A fitted transfer function model. Currently, only objects of class wa and pcr are supported.
method: character; type of cross-validation.
ncomp: numeric; number of components to fit, as in models with 1:ncomp components.
nboot: numeric; number of bootstrap samples.
nfold: numeric; number of chunks into which the training data are split. The k in k-fold.
folds: numeric; the number of times k-fold CV is performed.
verbose: logical; should progress of the CV be displayed?
...: Arguments passed to other methods.

Author

Gavin L. Simpson

Examples

Run this code

## Load the Imbrie & Kipp data and
## summer sea-surface temperatures
data(ImbrieKipp)
data(SumSST)
     
## fit the WA model
mod <- wa(SumSST ~., data = ImbrieKipp)
mod

## Leave one out CV
cv.loo <- crossval(mod)
cv.loo

## k-fold CV (k == 10)
cv.kfold <- crossval(mod, method = "kfold", kfold = 10, folds = 1)
cv.kfold

## n k-fold CV (k == 10, n = 10)
cv.nkfold <- crossval(mod, method = "kfold", kfold = 10, folds = 10)
cv.nkfold

## bootstrap with 100 bootstrap samples
cv.boot <- crossval(mod, method = "bootstrap", nboot = 100)
cv.boot

## extract fitted values and residuals
fitted(cv.boot)
resid(cv.boot)

## Principal Components Regression
mpcr <- pcr(SumSST ~., data = ImbrieKipp, ncomp = 10)
crossval(mpcr, method = "kfold", kfold = 10, folds = 2, ncomp = 10)

crossval(mpcr, method = "bootstrap", nboot = 100, ncomp = 10)