Normal aka Gaussian 1-d Mixture Models

Onedimensional Normal (i.e. Gaussian) Mixture Models (S3) Classes, for, e.g., density estimation or clustering algorithms research and teaching; providing the widely used Marron-Wand densities. Efficient random number generation and graphics. Fitting to data by efficient ML (Maximum Likelihood) or traditional EM estimation.

This is the result of some tinkering around at one time when investigating
yet another density estimation idea.
I found it useful to use normal mixtures as examples, including the
Marron-Wand densities.

			Martin Mächler, ETH Zurich, Switzerland
			March 1997,  June 2002
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o  The Marron-Wand densities are not regular data sets, e.g., they can't be
   used without the normix package. ==> hence in ./R/ and not ./data/

o  bug in qnorMix() --- the interval for uniroot is sometimes too small
   --> tests/ex.R  -- fixed fo 1.0-6

   HOWEVER: improve  qnorMix() for long input vectors:
     - sort(p)
     - compute  qnormMix( range(p) ) = qnorMix( p[c(1, n)] )
       use splinefun() in between as good starting values for uniroot()!