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analogue (version 0.17-7)

bootstrapObject: Bootstrap object description

Description

Objects of class bootstrap.mat are a complex containing many sub-components. This object is described here in more detail.

Arguments

Author

Gavin L. Simpson

Details

A large object is returned with some or all of the following depending on whether newdata and newenv are supplied or not.

observed:

vector of observed environmental values.

model:

a list containing the apparent or non-bootstrapped estimates for the training set. With the following components:

estimated:

estimated values for the response

residuals:

model residuals

r.squared:

Apparent \(R^2\) between observed and estimated values of response

avg.bias:

Average bias of the model residuals

max.bias:

Maximum bias of the model residuals

rmse:

Apparent error (RMSE) for the model.

k:

numeric; indicating the size of model used in estimates and predictions

bootstrap:

a list containing the bootstrap estimates for the training set. With the following components:

estimated:

Bootstrap estimates for the response

residuals:

Bootstrap residuals for the response

r.squared:

Bootstrap derived \(R^2\) between observed and estimated values of the response

avg.bias:

Average bias of the bootstrap derived model residuals

max.bias:

Maximum bias of the bootstrap derived model residuals

rmsep:

Bootstrap derived RMSEP for the model

s1:

Bootstrap derived S1 error component for the model

s2:

Bootstrap derived S2 error component for the model

k:

numeric; indicating the size of model used in estimates and predictions

sample.errors:

a list containing the bootstrap-derived sample specific errors for the training set. With the following components:

rmsep:

Bootstrap derived RMSEP for the training set samples

s1:

Bootstrap derived S1 error component for training set samples

s2:

Bootstrap derived S2 error component for training set samples

weighted:

logical; whether the weighted mean was used instead of the mean of the environment for k-closest analogues

auto:

logical; whether "k" was choosen automatically or user-selected

n.boot:

numeric; the number of bootstrap samples taken

call:

the matched call

type:

model type

predictions:

a list containing the apparent and bootstrap-derived estimates for the new data, with the following components:

observed:

the observed values for the new samples --- only if newenv is provided

model:

a list containing the apparent or non-bootstrapped estimates for the new samples. A list with the same components as model, above

bootstrap:

a list containing the bootstrap estimates for the new samples, with some or all of the same components as bootstrap, above

sample.errors:

a list containing the bootstrap-derived sample specific errors for the new samples, with some or all of the same components as sample.errors, above

See Also

mat, plot.mat, summary.bootstrap.mat, residuals