analogue (version 0.17-7)

predict.wa: Predict from a weighted average model

Description

Model predictions and cross-validation predictions for weighted averaging transfer function models.

Usage

# S3 method for wa
predict(object, newdata,
        CV = c("none", "LOO", "bootstrap", "nfold"),
        verbose = FALSE, n.boot = 100, nfold = 5, ...)

Value

An object of class "predict.wa", a list with the following components:

pred

A list with components pred and rmsep containing the predicted values and the sample specific errors if available.

performance

A list with model performance statistics.

model.pred

A list with components pred and rmsep containing the predicted values for the training set samples and the sample specific errors if available.

call

the matched function call.

CV.method

The CV method used.

Arguments

object

an object of class "wa", usually the result of a call to wa

newdata

An optional data frame in which to look for variables with which to predict. If omitted, the fitted values are used.

CV

Should cross-validation be performed? Leave-one-out ("LOO"), bootstrap ("bootstrap") and \(k\)-fold ("nfold") CV are currently available.

verbose

Should CV progress be printed to the console?

n.boot

The number of bootstrap samples or \(k\)-fold steps.

nfold

Number of subsets in \(k\)-fold CV.

...

further arguments passed to or from other methods.

Author

Gavin L. Simpson and Jari Oksanen (\(k\)-fold CV)

Details

Not all CV methods produce the same output. CV = "bootstrap" and CV = "nfold" produce sample specific errors.

References

Birks, H.J.B., Line, J.M., Juggins, S., Stevenson, A.C. and ter Braak, C.J.F. (1990). Diatoms and pH reconstruction. Philosophical Transactions of the Royal Society of London; Series B, 327; 263--278.

See Also

wa, predict.mat, performance, reconPlot.

Examples

## Imbrie and Kipp
data(ImbrieKipp)
ImbrieKipp <- ImbrieKipp / 100
data(SumSST)
ik.wa <- wa(SumSST ~ ., data = ImbrieKipp, tol.dw = TRUE,
            min.tol = 2, small.tol = "min")
ik.wa

## load V12.122 core data
data(V12.122)
V12.122 <- V12.122 / 100

## predict summer sea-surface temperature for V12.122 core
set.seed(2)
v12.pred <- predict(ik.wa, V12.122, CV = "bootstrap", n.boot = 100)

## draw the fitted reconstruction
reconPlot(v12.pred, use.labels = TRUE, display = "bars")

## extract the model performance stats
performance(v12.pred)