[R-sig-Geo] FW: Factor Analysis using R and grass

[Dylan Beaudette]

Hi,

Alternatively, if you must use all of the pixels in a massive grid, you can do 
PCA in GRASS with the i.pca command. Note that you must take care of 
standardization if you are using variables with different units / scales.

Cheers,

Dylan


On Wednesday 25 March 2009, Tomislav Hengl wrote:
> Hi Brian,
>
> The PCA you can also run without GRASS e.g.:
> > gridmaps <- readGDAL("NED1.asc")
> > names(gridmaps)[1] <- "DEM"
> > proj4string(gridmaps) <- CRS("+init=epsg:32618")
> > gridmaps$twi <- readGDAL("twi.asc")$band1
> > gridmaps$achan <- readGDAL("achan.asc")$band1
> > gridmaps$insolat <- readGDAL("insolat.asc")$band1
> > pc.dem <- prcomp(~DEM+twi+achan+insolat, scale=TRUE, gridmaps at data)
> > biplot(pc.dem, arrow.len=0.1, xlabs=rep(".", length(pc.dem$x[,1])),
> > main="PCA biplot")
>
> If you have missing pixels or if you use a max, then you will need to
> select the generated components before you can reproduce the maps.
>
> See also:
> http://spatial-analyst.net/wiki/index.php?title=Analysis_of_DEMs_in_R%2BILW
>IS/SAGA
>
> HTH
>
> Tom Hengl
> http://spatial-analyst.net
>
>
>
> -----Original Message-----
> From: r-sig-geo-bounces at stat.math.ethz.ch
> [mailto:r-sig-geo-bounces at stat.math.ethz.ch] On Behalf Of Brian Cooper
> Sent: Wednesday, March 25, 2009 2:27 PM
> To: r-sig-geo at stat.math.ethz.ch
> Subject: [R-sig-Geo] Factor Analysis using R and grass
>
> I am new to both R and Grass. I need to duplicate the Principal Component
> Analysis approach used in SPSS with GRASS and R. Is this possible?
>
> brian Cooper
>
> 	[[alternative HTML version deleted]]
>
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-- 
Dylan Beaudette
Soil Resource Laboratory
http://casoilresource.lawr.ucdavis.edu/
University of California at Davis
530.754.7341