Hi,
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
江鹏
Ph.D. Candidate
Antai College of Economics & Management
安泰经济管理学院
Department of Mathematics
数学系
Shanghai Jiaotong University (Minhang Campus)
800 Dongchuan Road
200240 Shanghai
P. R. China
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