search for: shiftx

I am looking for some help at removing low-frequency components from a signal, through Moving Average on a sliding window. I understand thiis is a smoothing procedure that I never done in my life before .. sigh. I searched R archives and found "rollmean", "MovingAverages {TTR}", "SymmetricMA". None of the above mantioned functions seems to accept the smoothing

Hi all, I have a very large binary vector, I wish to calculate the number of 1's over sliding windows. this is my very slow function slide<-function(seq,window){ n<-length(seq)-window tot<-c() tot[1]<-sum(seq[1:window]) for (i in 2:n) { tot[i]<- tot[i-1]-seq[i-1]+seq[i] } return(tot) } this works well for for reasonably sized vectors. Does

...t;-M[4,2]<-M[4,3] <- "flow" pp<-plotmat(M,pos=c(1,2,1),curve=0,name=names,lwd=1,box.lwd=2,cex.txt=0.8, box.type="circle",box.prop=1.0) # # diag(M) <- "self" pp<-plotmat(M,pos=c(2,2),curve=0,name=names,lwd=1,box.lwd=2,cex.txt=0.8, self.cex=0.5,self.shiftx=c(-0.1,0.1,-0.1,0.1), box.type="diamond",box.prop=0.5) M <- matrix(nrow=4,ncol=4,data=0) M[2,1]<-1 ;M[4,2]<-2;M[3,4]<-3;M[1,3]<-4 Col <- M Col[] <- "black" Col[4,2] <- "darkred" pp<-plotmat(M,pos=c(1,2,1),curve=0.2,name=names,lwd=1,box...