Perhaps: for(i in 1:100)assign(sprintf("Informative.data.class%s", i), rnorm(100, 0.25,1)) for(i in 1:100)assign(sprintf("Uninformative.data.class%s", i), rnorm(900))
Or working with a list: Informative <- replicate(100, rnorm(100, 0.25,1)) Uninformative <- replicate(100, rnorm(900)) On 06/02/2008, Nair, Murlidharan T <[EMAIL PROTECTED]> wrote: > I am trying to generate artificial data for feature selection. Basically > trying to generate a total of 1000 features with 100 that are informative and > rest are uninformative. > Informative.data.class1<-rnorm(100,0.25,1) > Uninformative.data.class1<-rnorm(900,0,1) > Informative.data.class2<-rnorm(100, -0.25,1) > Uninformative.data.class2<-rnorm(900,0,1) > > The above will give me one set of data for the two classes. I am interested > in generating about a 100 set for each class. What is a neat way to write it > in R? > Thanks ../Murli > > > [[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. > -- Henrique Dallazuanna Curitiba-Paraná-Brasil 25° 25' 40" S 49° 16' 22" O ______________________________________________ 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.