On Mon, 4 Oct 2004, Christian Hennig wrote:
Hi Michael,
Secondly, and perhaps more difficult, is a second data set. This, when plotted as a histogram, has two clear peaks, perhaps even three, all of which look as though they are normally distributed. So the theory is that my data set is actually made up of two, possibly three, underlying sub-sets of data which are normally distributed, but with different means and standard deviations. So 1) how do I test for this? And 2) how can I estimate the parameters (mean and SD) for the underlying distributions?
The answer to 2, as pointed out already, is to use EMclust in package mclust. Testing for the presence of a mixture is difficult from a theoretical point of view, and as far as I know, nothing is already implemented in R.
For testing for a mixture of two random variables there is the dip test of Hartigan---see diptest on CRAN
David Scott
_________________________________________________________________
David Scott Department of Statistics, Tamaki Campus
The University of Auckland, PB 92019
Auckland NEW ZEALAND
Phone: +64 9 373 7599 ext 86830 Fax: +64 9 373 7000
Email: [EMAIL PROTECTED]
Graduate Officer, Department of Statistics
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