Description Usage Arguments Value References

Compute the Expected Distance in Measure (EDM) between a kernel estimator-induced partition and the population one defined by a K-component normal mixture density for a single bandwidth value.

1 2 | ```
Edist.meas_singleh(n = 100, h, mus = 0, sigmas = 1, props = 1,
B = 100)
``` |

`n` |
sample size of the simulated Monte Carlo samples. |

`h` |
value of the bandwidth for which the EDM has to be computed. |

`mus` |
vector of means of the mixture components. |

`sigmas` |
vector of standard deviations of the mixture components. |

`props` |
vector of mixing proportions of the mixture components. |

`B` |
the number of Monte Carlo samples. |

the value of the EDM for the given value `h`

Chacón, J.E. (2015). A population background for nonparametric density-based clustering. Statistical Science 30(4): 518-532.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.