Description Usage Arguments Details Value Author(s) References Examples

Plot Bayesian information criterion (BIC) as a function of the number of clusters obtained from optimal univariate clustering results returned from `Ckmeans.1d.dp`

. The BIC normalized by sample size (BIC/n) is shown.

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`ck` |
an object of class |

`xlab` |
a character string. The x-axis label for the plot. |

`ylab` |
a character string. The x-axis label for the plot. |

`type` |
the type of plot to be drawn. See |

`main` |
a character string. The title for the plot. |

`sub` |
a character string. The subtitle for the plot. |

`...` |
arguments passed to |

The function visualizes the input data as sticks whose heights are the weights. It uses different colors to indicate optimal `k`-means clusters. The method to calcualte BIC based on Gaussian mixture models estimated on a univariate clustering is described in \insertCitesong2020wucCkmeans.1d.dp.

An object of class "`Ckmeans.1d.dp`

" defined in `Ckmeans.1d.dp`

.

Joe Song

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