[R] programming to calculate variance

2009-09-30 Thread marlene marchena
Dear R-user Suppose I have the following data y=c(2,1,5,8,11,3,1,7,50,21,33,7,60) x=data.frame(y) for(i in 4:nrow(x)) x[i,] =var(x[i-3:i-1,]) I'm trying to get a new variable with the variance of the 3 previous values (just an example) and with NA in the three first positions. I know that my

Re: [R] programming to calculate variance

2009-09-30 Thread Matthias Gondan
I think it should be var(y[i-3:i-1,]) instead of var(x[i-3:i-1,]) otherwise the values of the vector are overwritten Best wishes, Matthias marlene marchena schrieb: Dear R-user Suppose I have the following data y=c(2,1,5,8,11,3,1,7,50,21,33,7,60) x=data.frame(y) for(i in

Re: [R] programming to calculate variance

2009-09-30 Thread marlene marchena
Hi Petr, Thanks for your suggestion. It woks, but now I have other problem the positions of the values changed. I need the NA values in the three first positions. y=c(2,1,5,8,11,3,1,7,50,21,33,7,60) x=as.zoo(y) x 1 2 3 4 5 6 7 8 9 10 11 12 13 2 1 5 8 11 3 1 7 50 21 33 7 60

Re: [R] programming to calculate variance

2009-09-30 Thread Petr PIKAL
marlene marchena marchenamarl...@gmail.com napsal dne 30.09.2009 13:28:16: Hi Petr, Thanks for your suggestion. It woks, but now I have other problem the positions of the values changed. I need the NA values in the three first positions. y=c(2,1,5,8,11,3,1,7,50,21,33,7,60)

Re: [R] programming to calculate variance

2009-09-30 Thread Eik Vettorazzi
Hi Marlene, x=data.frame(y,vr=NA) for(i in 4:nrow(x)) x[i,vr] =var(y[(i-3):(i-1)]) will do the trick, solving both problems with overwriting subsequent x-values and obeying the precedence of R operators. For the latter, see ?Syntax and compare i-5 i-3:i-1 (i-3):(i-1) hth. marlene marchena

Re: [R] programming to calculate variance

2009-09-30 Thread marlene marchena
Thanks a lot, finally It works! I was wondering why my for() did not work. Now I now the difference between i-3 and (i-3) Thanks again for all your help. Marlene. x y vr 1 2 NA 2 1 NA 3 5 NA 4 8 4.33 5 11 12.33 6 3 9.00 7 1