# spc

##### 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`

##### Examples

```
# NOT RUN {
# 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 0.5-5, License: GPL*