So I know I must be missing something simple and obvious for the following
data manipulation where I have (in this example) 11 pairs of matrices
(gs4.0 to gs4.100 and ps1.0 to ps1.100) from some population simulations
(all with same dimensions) where I want to get some summary statistics on
the products of the cells in a pair (e.g., gs4.0 * ps1.0).  The code I
wrote below works fine, but it seems like there ought to be a simple way to
index the extensions on the names (.0 to .100) in a for loop to simplify
this code greatly.  I've spent some time trying various things using
paste() and assign() and have had no success.

mean.comb <- as.matrix(0:10,nrow = 11, ncol=1)
mean.comb <- cbind(mean.comb,0)

###to see list of files created
gs4files <- ls(pattern="gs4.*0")
ps1files <- ls(pattern="ps1.*0")

mean.comb[1,2] <- mean(apply(gs4.0 * ps1.0,1,sum))
mean.comb[2,2] <- mean(apply(gs4.10 * ps1.10,1,sum))
mean.comb[3,2] <- mean(apply(gs4.20 * ps1.20,1,sum))
mean.comb[4,2] <- mean(apply(gs4.30 * ps1.30,1,sum))
mean.comb[5,2] <- mean(apply(gs4.40 * ps1.40,1,sum))
mean.comb[6,2] <- mean(apply(gs4.50 * ps1.50,1,sum))
mean.comb[7,2] <- mean(apply(gs4.60 * ps1.60,1,sum))
mean.comb[8,2] <- mean(apply(gs4.70 * ps1.70,1,sum))
mean.comb[9,2] <- mean(apply(gs4.80 * ps1.80,1,sum))
mean.comb[10,2] <- mean(apply(gs4.90 * ps1.90,1,sum))
mean.comb[11,2] <- mean(apply(gs4.100 * ps1.100,1,sum))

mean.comb<- data.frame(mean.comb)
colnames(mean.comb) <- c("simulation", "mean.horses.removed")


Brian

Brian S. Cade, PhD

U. S. Geological Survey
Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO  80526-8818

email:  cadeb@usgs.gov <brian_cade@usgs.gov>
tel:  970 226-9326

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