In jstrunk001/RForInvt: Forest Inventory Data Compilation and FVS Growth Projections

multivariate aggregation

https://stackoverflow.com/questions/3367190/aggregate-and-weighted-mean-in-r

plyr approach

library(plyr)

#prep data
  set.seed(42)   # fix seed so that you get the same results
  n=10
  m=5
  dat = data.frame(plot=sort(rep(1:m,n)),baf=30,dbh = abs(rnorm(n*m)*10)+5) 
  dat$ba = 0.005454*dat$dbh^2
  dat$tpa = dat$baf / dat$ba

#aggregate - compute QMD using tpa weights
ddply(dat, .(plot), function(x) data.frame(qmd=sqrt(weighted.mean(x$dbh^2, x$tpa)) ))

#weighted mean diameter
ddply(dat, .(plot), function(x) data.frame(db_mn=weighted.mean(x$dbh, x$tpa) ))

data.table approach

library(data.table)
DT <- data.table(dat)
DT[,list(qmd = sqrt(weighted.mean(dbh^2,tpa))),by=plot]
DT[,list(mn_dbh = weighted.mean(dbh,tpa)),by=plot]

jstrunk001/RForInvt documentation built on April 17, 2025, 5:02 p.m.