| bootstrapObject {analogue} | R Documentation |
Bootstrap object description
Description
Objects of class bootstrap.mat are a complex containing
many sub-components. This object is described here in more detail.
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
"y", the
environment.
residuals: - model residuals.
r.squared: - Apparent 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.
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
"y".
residuals: - Bootstrap residuals for
"y".
r.squared: - Bootstrap derived R^2 between observed
and estimated values of
"y".
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.
Author(s)
Gavin L. Simpson
See Also
mat, plot.mat, summary.bootstrap.mat,
residuals
[Package
analogue version 0.4-3
Index]