Description Usage Arguments Details Value Author(s) References See Also Examples

Calculates highest density regions in one dimension

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`x` |
Numeric vector containing data. If |

`prob` |
Probability coverage required for HDRs |

`den` |
Density of data as list with components |

`h` |
Optional bandwidth for calculation of density. |

`lambda` |
Box-Cox transformation parameter where |

`nn` |
Number of random numbers used in computing f-alpha quantiles. |

`all.modes` |
Return all local modes or just the global mode? |

Either `x`

or `den`

must be provided. When `x`

is provided,
the density is estimated using kernel density estimation. A Box-Cox
transformation is used if `lambda!=1`

, as described in Wand, Marron and
Ruppert (1991). This allows the density estimate to be non-zero only on the
positive real line. The default kernel bandwidth `h`

is selected using
the algorithm of Samworth and Wand (2010).

Hyndman's (1996) density quantile algorithm is used for calculation.

A list of three components:

`hdr` |
The endpoints of each interval in each HDR |

`mode` |
The estimated mode of the density. |

`falpha` |
The value of the density at the boundaries of each HDR. |

Rob J Hyndman

Hyndman, R.J. (1996) Computing and graphing highest density
regions. *American Statistician*, **50**, 120-126.

Samworth, R.J. and Wand, M.P. (2010). Asymptotics and optimal bandwidth
selection for highest density region estimation. *The Annals of
Statistics*, **38**, 1767-1792.

Wand, M.P., Marron, J S., Ruppert, D. (1991) Transformations in density
estimation. *Journal of the American Statistical Association*,
**86**, 343-353.

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