[R] Generating correlated data from uniform distribution
Ken Knoblauch
knoblauch at lyon.inserm.fr
Sat Jul 2 09:06:48 CEST 2005
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))
--
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Ken Knoblauch
Inserm U371, Cerveau et Vision
Department of Cognitive Neurosciences
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France
tel: +33 (0)4 72 91 34 77
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