summary.bootstrap.mat {analogue}  R Documentation 
Summarise bootstrap resampling for MAT models
Description
summary
method for class "bootstrap.mat"
.
Usage
## S3 method for class 'bootstrap.mat'
summary(object, ...)
Arguments
object 
an object of class "bootstrap.mat" , usually the
result of a call to bootstrap.mat .

... 
arguments passed to or from other methods.

Value
A data frame with the following components:
observed 
vector of observed environmental values.

model 
a list containing the apparent or nonbootstrapped
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

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 bootstrapderived 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 kclosest analogues

auto 
logical; whether k was choosen automatically or
userselected

n.boot 
numeric; the number of bootstrap samples taken

call 
the matched call

call 
model type

predictions 
a list containing the apparent and
bootstrapderived 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
nonbootstrapped 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 bootstrapderived
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
bootstrap.mat
, mat
,
summary
.
Examples
## Not run:
## 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)
## End(Not run)
[Package
analogue version 0.176
Index]