`vimixUniGauss.Rd`

Variational Bayesian inference for unsupervised clustering, mixture of univariate Gaussians

vimixUniGauss(X, K, prior, init = "kmeans", tol = 1e-19, maxiter = 2000, verbose = F)

X | NxD data matrix. |
---|---|

K | (Maximum) number of clusters. |

prior | Prior parameters (optional). |

init | Initialisation method (optional). If it is a vector, it is interpreted as the vector of initial cluster allocations. If it is a string, it is interpreted as the name of the clustering algorithm used for the initialisation (only "kmeans" and "random") available at the moment). |

tol | Tolerance on lower bound. Default is 10e-20. |

maxiter | Maximum number of iterations of the VB algorithm. Default is 2000. |

verbose | Boolean flag which, if TRUE, prints the iteration numbers. Default is FALSE. |

A list containing L, the lower bound at each step of the algorithm, label, a vector containing the cluster labels, model, a list containing the trained model structure.

Bishop, C.M., 2006. Pattern recognition and machine learning. Springer.