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A useful point is the\ngeneric fit() method for each class, which uses a maximum\nlikelihood estimation to find the parameters of a dataset, see,\ne.g. Hastie, T. and al (2009) .\nFurthermore, the rv_histogram class gives a non-parametric fit,\nwith the same accessors that for the classic distribution.\nFinally, three random generators useful to build synthetic data\nare given: a multivariate normal generator, an orthogonal\nmatrix generator, and a symmetric positive definite matrix\ngenerator, see Mezzadri, F. 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