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.
1 2 3 4 5 6 7 8 |
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
1 2 3 4 5 6 7 8 9 10 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.