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

Plots univariate density with highest density regions displayed

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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 |

`xlab` |
Label for x-axis. |

`ylab` |
Label for y-axis. |

`ylim` |
Limits for y-axis. |

`plot.lines` |
If |

`col` |
Colours for regions. |

`bgcol` |
Colours for the background behind the boxes. Default |

`legend` |
If |

`...` |
Other arguments passed to plot. |

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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