Generic plot function for CAST Classes

A plotting function for a forward feature selection result. Each point is the mean performance of a model run. Error bars represent the standard errors from cross validation. Marked points show the best model from each number of variables until a further variable could not improve the results. If type=="selected", the contribution of the selected variables to the model performance is shown.

Density plot of nearest neighbor distances in geographic space or feature space between training data as well as between training data and prediction locations. Optional, the nearest neighbor distances between training data and test data or between training data and CV iterations is shown. The plot can be used to check the suitability of a chosen CV method to be representative to estimate map accuracy.

Plot the DI/LPD and errormetric from Cross-Validation with the modeled relationship

## Usage

```
# S3 method for trainDI
plot(x, ...)
# S3 method for aoa
plot(x, samplesize = 1000, variable = "DI", ...)
# S3 method for nndm
plot(x, type = "strict", stat = "ecdf", ...)
# S3 method for knndm
plot(x, type = "strict", stat = "ecdf", ...)
# S3 method for ffs
plot(
x,
plotType = "all",
palette = rainbow,
reverse = FALSE,
marker = "black",
size = 1.5,
lwd = 0.5,
pch = 21,
...
)
# S3 method for geodist
plot(x, unit = "m", stat = "density", ...)
# S3 method for errorModel
plot(x, ...)
```

## Arguments

- x
errorModel, see

`DItoErrormetric`

- ...
other params

- samplesize
numeric. How many prediction samples should be plotted?

- variable
character. Variable for which to generate the density plot. 'DI' or 'LPD'

- type
String, defaults to "strict" to show the original nearest neighbour distance definitions in the legend. Alternatively, set to "simple" to have more intuitive labels.

- stat
"density" for density plot or "ecdf" for empirical cumulative distribution function plot.

- plotType
character. Either "all" or "selected"

- palette
A color palette

- reverse
Character. Should the palette be reversed?

- marker
Character. Color to mark the best models

- size
Numeric. Size of the points

- lwd
Numeric. Width of the error bars

- pch
Numeric. Type of point marking the best models

- unit
character. Only if type=="geo" and only applied to the plot. Supported: "m" or "km".

## Examples

```
if (FALSE) {
data(splotdata)
splotdata <- st_drop_geometry(splotdata)
ffsmodel <- ffs(splotdata[,6:16], splotdata$Species_richness, ntree = 10)
plot(ffsmodel)
#plot performance of selected variables only:
plot(ffsmodel,plotType="selected")
}
```