createMixtureTarget(mixturesample, mixturesize, ncomponents, mixtureparameters)"vector": data set to be used. If not provided, a synthetic data set is generated."numeric": represents the data set size if a data set is to be generated."numeric": represents the fixed number of components to be used."list": provides the parameters to be used if a data set has to be generated.
The parameters include the number of components, the component weights, means and variances.target-class, with a name, a dimension, a function giving the log density,
a function to generate sample from the distribution, parameters of the distribution, and a function to draw init points for
the MCMC algorithms. The log density involves a likelihood and a prior, and the prior is as in Richardson and Green, "On Bayesian
analysis of mixtures with an unknown number of components", published in JRSS B, 1997.
target-class, createTrimodalTarget