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 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

### Author(s)

Gavin L. Simpson

### See Also

`mat`

, `plot.mat`

, `summary.bootstrap.mat`

,
`residuals`

*analogue*version 0.17-6 Index]