While you are looking at weird distributions, here is one that we have used in experiments on noise masking to explore the bandwidth of visual mechanisms
D'Zmura, M., & Knoblauch, K. (1998). Spectral bandwidths for the detection of color. Vision Research, 20, 3117-28 and G. Monaci, G. Menegaz, S. Susstrunk and K. Knoblauch Chromatic Contrast Detection in Spatial Chromatic Noise Visual Neuroscience, Vol. 21, No 3, pp. 291-294, 2004 N <- 10000 x <- runif(N, -.5,.5) y <- runif(N, -abs(x), abs(x)) plot(x,y) y is not uniform but it is conditional on x. The plot reveals why we called this "sectored noise". HTH ken -------------------------------------------------------- "Jim Brennan" <jfbrennan at rogers.com> writes: > Yes you are right I guess this works only for normal data. Free advice > sometimes comes with too little consideration :-) Worth every cent... > Sorry about that and thanks to Spencer for the correct way. Hmm, but is it? Or rather, what is the relation between the correlation of the normals and that of the transformed variables? Looks nontrivial to me. Incidentally, here's a way that satisfies the criteria, but in a rather weird way: N <- 10000 rho <- .6 x <- runif(N, -.5,.5) y <- x * sample(c(1,-1), N, replace=T, prob=c((1+rho)/2,(1-rho)/2)) -- O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907 ____________________ Ken Knoblauch Inserm U371, Cerveau et Vision Department of Cognitive Neurosciences 18 avenue du Doyen Lepine 69500 Bron France tel: +33 (0)4 72 91 34 77 fax: +33 (0)4 72 91 34 61 portable: 06 84 10 64 10 http://www.lyon.inserm.fr/371/ ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
