[R] simulating Gaussian Mixture Method

From: Peng Jiang <jp021_at_sjtu.edu.cn>
Date: Mon, 16 Jun 2008 13:48:22 +0800


  I have a mixture pdf which has three components, each satisfies the 6 dimension normal distribution.

   I use mvrnorm() from the MASS library to generate 1000 samples for each component and I add them
  to get the random samples which satisfies with the mixture distribution.

  I use Mclust() from the mclust library to get the model of the samples and strange things happened.
  First it gave a warning

> samplesMclust <- Mclust( samples )

  Warning messages:
1: In summary.mclustBIC(Bic, data, G = G, modelNames = modelNames) :

   best model occurs at the min or max # of components considered 2: In Mclust(samples) : optimal number of clusters occurs at min choice

Then I input
> samplesMclust

  best model: XXI with 1 components

  it says the best model is with 1 component !

   I am confused ... Is it because the way that I generate samples is wrong???

   thanks so much !

Peng Jiang
Ph.D. Candidate

Antai College of Economics & Management
Department of Mathematics
Shanghai Jiaotong University (Minhang Campus) 800 Dongchuan Road
200240 Shanghai
P. R. China

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