Simulated Datasets used in Baudry et al. (2010) to illustrate the proposed mixture components combining method for clustering.
Please see the cited article for a detailed presentation of these datasets. The data frame with name exN.M is presented in Section N.M in the paper.
Test1D (not in the article) has been simulated from a Gaussian mixture distribution in R.
ex4.1 and ex4.2 have been simulated from a Gaussian mixture distribution in R^2.
ex4.3 has been simulated from a mixture of a uniform distribution on a square and a spherical Gaussian distribution in R^2.
ex4.4.1 has been simulated from a Gaussian mixture model in R^2
ex4.4.2 has been simulated from a mixture of two uniform distributions in R^3.
ex4.1 is a data frame with 600 observations of 2 real variables.
ex4.2 is a data frame with 600 observations of 2 real variables.
ex4.3 is a data frame with 200 observations of 2 real variables.
ex4.4.1 is a data frame with 800 observations of 2 real variables.
ex4.4.2 is a data frame with 300 observations of 3 real variables.
Test1D is a data frame with 200 observations of 1 real variable.
J.-P. Baudry, A. E. Raftery, G. Celeux, K. Lo and R. Gottardo (2010). Combining mixture components for clustering. Journal of Computational and Graphical Statistics, 19(2):332-353.
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set.seed(1) data(Baudry_etal_2010_JCGS_examples) output <- mixmodCombi(ex4.4.2, nbCluster = 1:10, models = mixmodGaussianModel(listModels = "Gaussian_pk_Lk_Ck")) output # is of class MixmodCombi ## Not run: plot(output) # plots the hierarchy of combined solutions, then some "entropy plots" # which may help to select the number of classes ## End(Not run)
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