summary
method for class "bootstrap.mat"
.
# S3 method for bootstrap.mat
summary(object, ...)
A data frame with the following components:
vector of observed environmental values.
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 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
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
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
logical; whether the weighted mean was used instead of the mean of the environment for k-closest analogues
logical; whether k
was choosen automatically or
user-selected
numeric; the number of bootstrap samples taken
the matched call
model type
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 apparent
, 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
an object of class "bootstrap.mat"
, usually the
result of a call to bootstrap.mat
.
arguments passed to or from other methods.
Gavin L. Simpson
bootstrap.mat
, mat
,
summary
.
if (FALSE) {
## continue the RLGH example from ?join
example(join)
## fit the MAT model using the squared chord distance measure
swap.mat <- mat(swapdiat, swappH, method = "SQchord")
## bootstrap training set
swap.boot <- bootstrap(swap.mat, k = 10, n.boot = 100)
swap.boot
summary(swap.boot)
}
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