| icasamp {ica} | R Documentation |
Sample observations from the 18 source signal distributions used in Bach and Jordan (2002). Can also return density values and kurtosis for each distribution. Use icaplot to plot distributions.
icasamp(dname,query=c("rnd","pdf","kur"),nsamp=NULL,data=NULL)
dname |
Distribution name: letter "a" through "r" (see Bach & Jordan, 2002). |
query |
What to return: |
nsamp |
Number of observations to sample. Only used if |
data |
Data values for density evaluation. Only used if |
Inspired by usr_distrib.m from Bach's (2002) kernel-ica MATLAB toolbox.
If query="rnd", returns random sample of size nsamp.
If query="pdf", returns density for input data.
If query="kur", returns kurtosis of distribution.
Nathaniel E. Helwig <helwig@umn.edu>
Bach, F.R. (2002). kernel-ica. MATLAB toolbox (ver 1.2) http://www.di.ens.fr/~fbach/kernel-ica/.
Bach, F.R. & Jordan, M.I. (2002). Kernel independent component analysis. Journal of Machine Learning Research, 3, 1-48.
########## EXAMPLE ##########
# sample 1000 observations from distribution "f"
set.seed(123)
mysamp <- icasamp("f","rnd",nsamp=1000)
xr <- range(mysamp)
hist(mysamp,freq=FALSE,ylim=c(0,.8),breaks=sqrt(1000))
# evaluate density of distribution "f"
xseq <- seq(-5,5,length.out=1000)
mypdf <- icasamp("f","pdf",data=xseq)
lines(xseq,mypdf)
# evaluate kurtosis of distribution "f"
icasamp("f","kur")