analogue (version 0.10-0)

predict.mat: Predict method for Modern Analogue Technique models

Description

Predicted values based on a MAT model object.

Usage

## S3 method for class 'mat':
predict(object, newdata, k, weighted = FALSE,
        bootstrap = FALSE, n.boot = 1000,
        probs = c(0.01, 0.025, 0.05, 0.1), ...)

Arguments

object

an object of mat.

newdata

data frame; required only if predictions for some new data are required. Mst have the same number of columns, in same order, as x in mat. See example below or

k

number of analogues to use. If missing, k is chosen automatically as the k that achieves lowest RMSE.

weighted

logical; should the analysis use the weighted mean of environmental data of analogues as predicted values?

bootstrap

logical; should bootstrap derived estimates and sample specific errors be calculated-ignored if newdata is missing.

n.boot

numeric; the number of bootstrap samples to take.

probs

numeric; vector of probabilities with values in [0,1].

...

arguments passed to of from other methods.

Value

• A object of class predict.mat is returned if newdata is supplied, otherwise an object of fitted.mat is returned. If bootstrap = FALSE then not all components will be returned.
• observed
  vector of observed environmental values.
• model
  a list containing the model or non-bootstrapped estimates for the training set. With the following components:

  • estimated

  {estimated values for "y", the environment.} residuals{model residuals.} r.squared{Model $R^2$ between observed and estimated values of "y".} avg.bias{Average bias of the model residuals.} max.bias{Maximum bias of the model residuals.} rmsep{Model error (RMSEP).} k{numeric; indicating the size of model used in estimates and predictions.}

item

• bootstrap
• residuals
• r.squared
• avg.bias
• max.bias
• rmsep
• s1
• s2
• k
• sample.errors
• s1
• s2
• weighted
• auto
• n.boot
• predictions
• model
• bootstrap
• sample.errors
• method
• quantiles
• minDC
• Dij

itemize

• observed

code

newdata

eqn

$R^2$

emph

k

Details

This function returns one or more of three sets of results depending on the supplied arguments: [object Object],[object Object],[object Object] The latter is simply a wrapper for bootstrap(model, newdata, ...) - see bootstrap.mat.

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

mat, bootstrap.mat

Examples

## Imbrie and Kipp example
## load the example data
data(ImbrieKipp)
data(SumSST)
data(V12.122)

## merge training and test set on columns
dat <- join(ImbrieKipp, V12.122, verbose = TRUE)

## extract the merged data sets and convert to proportions
ImbrieKipp <- dat[[1]] / 100
V12.122 <- dat[[2]] / 100

## fit the MAT model using the chord distance measure
(ik.mat <- mat(ImbrieKipp, SumSST, method = "chord"))

## predict for V12.122 data
predict(ik.mat, V12.122)