spc

0th

Percentile

Derive Spatial Predictive Components

Derives Spatial Predictive Components for a given set of covariates. It wraps the stats::prcomp method and predicts a list principal components for an object of type "SpatialPixelsDataFrame".

Keywords
methods
Usage
# S4 method for SpatialPixelsDataFrame,formula
spc(obj, formulaString, scale. = TRUE, 
      silent = FALSE, …)
# S4 method for list,list
spc(obj, formulaString, scale. = TRUE, 
      silent = FALSE, …)
Arguments
obj
object of class "SpatialPixelsDataFrame" (must contain at least two grids) or a list of objects of type "SpatialPixelsDataFrame"
formulaString
object of class "formula" or a list of formulas
scale.
object of class "logical"; specifies whether covariates need to be scaled
silent
object of class "logical"; specifies whether to print the progress
additional arguments that can be passed to stats::prcomp
Value

spc returns an object of type "SpatialComponents". This is a list of grids with generic names PC1,…,PCp, where p is the total number of input grids.

Note

This method assumes that the input covariates are cross-correlated and hence their overlap can be reduced. The input variables are scaled by default and the missing values will be replaced with 0 values to reduce loss of data due to missing pixels. This operation can be time consuming for large grids.

See Also

stats::prcomp, SpatialComponents-class

Aliases
  • spc
  • spc,SpatialPixelsDataFrame,formula-method
  • spc,list,list-method
Examples
# load data:
library(plotKML)
library(sp)

pal = rev(rainbow(65)[1:48])
data(eberg_grid)
gridded(eberg_grid) <- ~x+y
proj4string(eberg_grid) <- CRS("+init=epsg:31467")
formulaString <- ~ PRMGEO6+DEMSRT6+TWISRT6+TIRAST6
eberg_spc <- spc(eberg_grid, formulaString)
names(eberg_spc@predicted) # 11 components on the end;
## Not run: ------------------------------------
# # plot maps:
# rd = range(eberg_spc@predicted@data[,1], na.rm=TRUE)
# sq = seq(rd[1], rd[2], length.out=48)
# spplot(eberg_spc@predicted[1:4], at=sq, col.regions=pal)
## ---------------------------------------------
Documentation reproduced from package GSIF, version 0.5-4, License: GPL

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