Hi Julia, In addition to Martyn's answer and David's friendly post I'd just add that it's not a good idea to call a variable "c" since the function of that name is so often used in R.
Michael On 7 October 2010 22:28, Martyn Byng <martyn.b...@nag.co.uk> wrote: > Hi, > > Your code is of the form > > for (i in 1:nsim) { > ## Do something that generates variable qf05 > > M <- coeff(qf05) > } > > This means that you are overwriting the variable M at each iteration and > so when the loop has finished you only have the coefficients from the > last simulation. There are lots of ways of getting around this, the > easiest would probably be to do something like > > M <- matrix(0,nsim,2) > for (i in 1:nsim) { > ## Do something that generates variable qf05 > > M[i,] <- coeff(qf05) > } > > then M would be a nsim by 2 matrix, with each row holding the > coefficients from a different simulation. You could also look at > removing the loop by vectorising the code. > > Hope this helps > > Martyn > > > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] > On Behalf Of Julia Lira > Sent: 07 October 2010 11:40 > To: r-help@r-project.org > Subject: [R] quantile regression > > > Dear all, > > > > I am a new user in r and I am facing some problems with the quantile > regression specification. I have two matrix (mresultb and mresultx) with > nrow=1000 and ncol=nsim, where I specify (let's say) nsim=10. Hence, the > columns in my matrix represents each simulation of a determined > variable. I need to regress each column of mresultb on mresultx. My > codes are the following: > > > > set.seed(180185) > nsim <- 10 > mresultx <- matrix(-99, nrow=1000, ncol=nsim) > mresultb <- matrix(-99, nrow=1000, ncol=nsim) > for (i in 1:nsim){ > # make a matrix with 5 cols of N random uniform values > N <- 200 > I <- 5 > u <- replicate( 5, runif(N, 0, 1) ) > # fit matrix u in another matrix of 1 column > mu <- matrix(u, nrow=1000, ncol=1) > # make auction-specific covariate > x <- runif(N, 0, 1) > mx <- matrix(rep(x,5), nrow=1000, ncol=1) > b0 <- matrix(rep(c(1),1000), nrow=1000, ncol=1) > #function for private cost > c <- b0+b0*mx+mu > #bidding strategy > b <- mx+((I+1)/I)+((I-1)/I)*mu > mresultb[,i] <- b > mresultx[,i] <- mx > qf05 <- rq(formula = mresultb[,i] ~ mresultx[,i], tau=0.5) > M <- coef(qf05) > } > > > But I just can see the quantile regression coefficients for 1 > simulation, not for each i. > > Maybe this is a stupid question, but i am not so familiar with this > software yet. > > > > Thanks in advance! > > > > Julia > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > ________________________________________________________________________ > This e-mail has been scanned for all viruses by Star.\ _...{{dropped:12}} > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.