I am working with a matrix (x),
where rows are non-overlapping geographical areas (postcodes; here denoted with letter row names),
and columns are income bands with a central value (e.g. £7.5k, here denoted x1,x2, etc.).
The data are counts (how many households with 0-5k pa, 5-10k pa?, etc.)
I would like to summarise this data set.
First row-wise as suggested by Henrik Bengtsson (www.maths.lth.se/help/R/R.classes/ <http://www.maths.lth.se/help/R/R.classes/> ), example:
library (R.basic)
x<-cbind(x1=3,x2=c(4:1,2:5))
dimnames(x)[[1]]<-letters[1:8]
w<-c(1,2)
wm <- apply(x, MARGIN=1, FUN=weighted.median, w=w, na.rm=TRUE)
wm
QUESTION
Secondly, I would like to aggregate rows (postcodes) into bigger units according additional factor vectors (higher administrative order or environmental attributes).
I would be grateful for ideas to how I can achieve this in our R.
Jakob
Software:
R ver 2.01 (Windows)
R.basic ver 0.59
Jakob Petersen
GISc student (MSc)
Birkbeck, University of London
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