Dear List-Members, I have a problem with the function lqs() from package MASS. In some cases it produces different results for the same settings and needs a random seed to be set, in other cases not. I really cannot understand, why this happens. As well I do not understand what exactly you need the random seed for. Is it a starting point for iterations? Or do different results occur because of the estimation doesn't converge?
I tried data "phones" from package MASS. You find this example as well in the MASS-book on page 160. > lqs(calls~year, data=phones, method="lms") Call: lqs.formula(formula = calls ~ year, data = phones, method = "lms") Coefficients: (Intercept) year -55.947 1.155 Scale estimates 0.9377 0.9095 > > lqs(calls~year, data=phones, method="S") Call: lqs.formula(formula = calls ~ year, data = phones, method = "S") Coefficients: (Intercept) year -52.5 1.1 Scale estimates 2.129 You can do it over and over again and get the same coefficients. In contrast, if u use other data like cats from MASS or simulated data, u get different outputs every time u start the code if not electing a random.seed. > lqs(Hwt~Bwt, data=cats, method="S") Call: lqs.formula(formula = Hwt ~ Bwt, data = cats, method = "S") Coefficients: (Intercept) Bwt 0.2625 3.6250 Scale estimates 1.474 > lqs(Hwt~Bwt, data=cats, method="S") Call: lqs.formula(formula = Hwt ~ Bwt, data = cats, method = "S") Coefficients: (Intercept) Bwt 0.4714 3.5714 Scale estimates 1.474 Example with simulated data: > b0<--1 > b1<-6 > b2<-0.8 > b3<--0.5 > > x1<-runif(200,-3,3) > x2<-runif(200,20,40) > x3<-rbinom(200, 1, 0.7) > e<-rnorm(200,0,1) > y<-b0+b1*x1+b2*x2+b3*x3+e > lqs(y~x1, method="lms") Call: lqs.formula(formula = y ~ x1, method = "lms") Coefficients: (Intercept) x1 22.239 4.964 Scale estimates 5.379 4.891 > > lqs(y~x1, method="S") Call: lqs.formula(formula = y ~ x1, method = "S") Coefficients: (Intercept) x1 23.193 5.743 Scale estimates 5.642 > lqs(y~x1, method="lms") Call: lqs.formula(formula = y ~ x1, method = "lms") Coefficients: (Intercept) x1 21.176 5.255 Scale estimates 5.383 5.023 > > lqs(y~x1, method="S") Call: lqs.formula(formula = y ~ x1, method = "S") Coefficients: (Intercept) x1 22.55 5.46 Scale estimates 5.642 Thanks for your help, I appreciate it! K. Schmidt ________________________________________________________________ Neu: WEB.DE Doppel-FLAT mit Internet-Flatrate + Telefon-Flatrate für nur 19,99 Euro/mtl.!* http://produkte.web.de/go/02/ ______________________________________________ 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.