CENFA: GLcenfa – R documentation

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GLcenfa

Climate-niche factor analysis for reference study area

Description

This function is used to facilitate comparisons between species in the same study area. It speeds up the computation of multiple CNFAs or ENFAs by calculating the global covariance matrix as a first step, which can then be fed into the cnfa or enfa functions as their first argument. This saves the user from having to calculate the global covariance matrix for each species, which can take quite a bit of time.

Usage

GLcenfa(
  x,
  center = TRUE,
  scale = TRUE,
  filename = "",
  progress = FALSE,
  parallel = FALSE,
  n = 1,
  cl = NULL,
  keep.open = FALSE,
  ...
)

## S4 method for signature 'Raster'
GLcenfa(
  x,
  center = TRUE,
  scale = TRUE,
  filename = "",
  progress = FALSE,
  parallel = FALSE,
  n = 1,
  cl = NULL,
  keep.open = FALSE,
  ...
)

Arguments

`x`	Raster* object, typically a brick or stack of p environmental raster layers
`center`	logical or numeric. If `TRUE`, centering is done by subtracting the layer means (omitting NAs), and if `FALSE`, no centering is done. If `center` is a numeric vector with length equal to the `nlayers(x)`, then each layer of `x` has the corresponding value from center subtracted from it
`scale`	logical or numeric. If `TRUE`, scaling is done by dividing the (centered) layers of `x` by their standard deviations if center is `TRUE`, and the root mean square otherwise. If scale is `FALSE`, no scaling is done. If scale is a numeric vector with length equal to `nlayers(x)`, each layer of `x` is divided by the corresponding value. Scaling is done after centering
`filename`	character. Optional filename to save the RasterBrick output to file. If this is not provided, a temporary file will be created for large `x`
`progress`	logical. If `TRUE`, messages and progress bar will be printed
`parallel`	logical. If `TRUE` then multiple cores are utilized
`n`	numeric. Number of CPU cores to utilize for parallel processing
`cl`	optional cluster object
`keep.open`	logical. If `TRUE` and `parallel = TRUE`, the cluster object will not be closed after the function has finished
`...`	Additional arguments for `writeRaster`

Details

If there is too much correlation between the layers of x, the covariance matrix will be singular, which will lead to later problems in computing the overall marginalities, sensitivities, or specializations of species. In this case, a warning will be issued, suggesting the removal of correlated variables or a transformation of the data.

Value

Returns an S4 object of class GLcenfa with the following components:

global_ras: Raster* x of p layers, possibly centered and scaled
cov: Global p x p covariance matrix

Examples

glc <- GLcenfa(x = climdat.hist)

CENFA

Climate and Ecological Niche Factor Analysis

v1.1.0

GPL (>= 3)

Authors

D. Scott Rinnan

Initial release

2020-02-15