prcomp: SpatRaster PCA with prcomp
In terra: Spatial Data Analysis

prcomp

R Documentation

SpatRaster PCA with prcomp

Description

Compute principal components for SpatRaster layers. This method may be preferred to princomp for its greater numerical accuracy. However, it is slower and for very large rasters it can only be done with a sample. This may be good enough but see princomp if you want to use all values. Unlike princomp, in this method the sample variances are used with n-1 as the denominator.

Usage

## S4 method for signature 'SpatRaster'
prcomp(x, retx=TRUE, center=TRUE, scale.=FALSE, 
		tol=NULL, rank.=NULL, maxcell=Inf)

Arguments

`x`	SpatRaster
`retx`	a logical value indicating whether the rotated variables should be returned
`center`	a logical value indicating whether the variables should be shifted to be zero centered. Alternately, a vector of length equal the number of columns of x can be supplied. The value is passed to `scale`
`scale.`	a logical value indicating whether the variables should be scaled to have unit variance before the analysis takes place. The default is FALSE for consistency with S, but in general scaling is advisable. Alternatively, a vector of length equal the number of columns of x can be supplied. The value is passed to `scale`
`tol`	a value indicating the magnitude below which components should be omitted. (Components are omitted if their standard deviations are less than or equal to tol times the standard deviation of the first component.) With the default null setting, no components are omitted (unless `rank.` is specified less than `min(dim(x))`). Other settings for `tol` could be `tol = 0` or `tol = sqrt(.Machine$double.eps)`, which would omit essentially constant components
`rank.`	optionally, a number specifying the maximal rank, i.e., maximal number of principal components to be used. Can be set as alternative or in addition to tol, useful notably when the desired rank is considerably smaller than the dimensions of the matrix
`maxcell`	positive integer. The maximum number of cells to be used. If this is smaller than ncell(x), a regular sample of `x` is used

Value

prcomp object

Note

prcomp may change the layer names if they are not valid. See make.names. In that case, you will get a warning, and would need to also make the layer names of x valid before using predict. Even better would be to change them before calling prcomp.

Examples

f <- system.file("ex/logo.tif", package = "terra")
r <- rast(f)
pca <- prcomp(r)
x <- predict(r, pca)

# use "index" to get a subset of the components
p <- predict(r, pca, index=1:2)

terra documentation built on Oct. 14, 2024, 5:07 p.m.