Calculating descriptive stats from many maps
Dear Rainer, This is of course possible in R, and can be done in several ways: 1) for example, you can derive the average value using the rowSums function:
maps$Nsum <- rowSums(maps at data, na.rm=T, dims=1) maps$avg <- maps$Nsum/(length(names(meuse.grid at data))-1)
You could also loop the sd, mean and quantile function over a range of cells:
for(i in length(names(maps at data))) {
maps at data$sd[i] <- sd(maps at data[i,])
maps at data$mean[i] <- mean(maps at data[i,])
...
}
This could take a lot of time! 2) if your maps are rather large, try also using the SAGA function:
rsaga.get.usage(lib = "geostatistics_grid", module=5)
SAGA CMD 2.0.3 library path: C:/Progra~1/saga_vc/modules library name: geostatistics_grid module name : Statistics for Grids This is probably the fastest method you can use. HTH T. Hengl
-----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 Rainer M Krug Sent: Monday, February 09, 2009 4:58 PM To: R-sig-Geo at stat.math.ethz.ch Subject: [R-sig-Geo] Calculating descriptive stats from many maps Hi I have 25000 maps, generated by simulation predictions, covering the same area, and would like to calculate some descriptive stats, like mean, standard deviation, median, quartiles of all cells, to create a "variability map". Is there an easy way of doing this in R? Thanks, Rainer -- Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology, UCT), Dipl. Phys. (Germany) Centre of Excellence for Invasion Biology Faculty of Science Natural Sciences Building Private Bag X1 University of Stellenbosch Matieland 7602 South Africa
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