search for: wsums

...in a given interval. Given equal-length vectors of data 'data' and weights 'w', and breaks (intervals) for the histogram, I calculate a weighted histogram as follows (see MASS's 'truehist' for an unweighted histogram): bin <- cut(data, breaks, include.lowest = TRUE) wsums <- sapply(split( w, f = bin), sum) prob <- wsums/(diff(breaks) * sum(w)) where 'bin' is the recoded data vector, 'wsums' is the sum of weights across each factor in 'bin', and 'prob' is the vector of probabilities used to plot the true histogram. But if...

Is there a weighted median function out there similar to weighted.mean() but for medians? If not, I'll try implement or port it myself. The need for a weighted median came from the following optimization problem: x* = arg_x min (a|x| + sum_{k=1}^n |x - b_k|) where a : is a *positive* real scalar x : is a real scalar n : is an integer b_k: are negative and positive scalars

..., > here is a one-liner for a df without the rowSum column > > df<-data.frame(id=c("x01","x02","x03","x04","x05","x06"),a=c(1,2,NA,4,5,6),b=c(2,4,6,8,10,NA),c=c(NA,3,9,12,NA,NA)) > > (df$wSum<-apply(sweep(df[,-1],1,rowSums(df[,-1],na.rm=T),"/"),1,function(x)sum(x*w,na.rm=T))) > > hth. > > Am 06.02.2013 14:17, schrieb D. Alain: > > Dear R-List, > > > > > > I am sure there must be a very simple way to do this - I just do not know how... > > This is what I want to...

Dear R-List, I am sure there must be a very simple way to do this - I just do not know how... This is what I want to do: #my dataframe df<-data.frame(id=c("x01","x02","x03","x04","x05","x06"),a=c(1,2,NA,4,5,6),b=c(2,4,6,8,10,NA),c=c(NA,3,9,12,NA,NA),sum=c(3,9,15,24,15,6))    id    a     b     c   sum 1 x01  1     2    NA   3 2