hdrbw

Estimates the optimal bandwidth for 1-dimensional highest density regions

distribution

smooth

Computation of highest density regions in one and two dimensions, kernel estimation of univariate density functions conditional on one covariate,and multimodal regression.

Rob Hyndman

hdrcde

Highest Density Regions and Conditional Density Estimation

Jochen Einbeck

Matthew Wand

Simon Carrignon

Fan Cheng

hdrbw function

<dl><dt>x</dt>
<dd>Numerical vector containing data.</dd>
<dt>HDRlevel</dt>
<dd>HDR-level as defined in Hyndman (1996). Setting `HDRlevel'
equal to p (0&lt;p&lt;1) corresponds to a probability of 1-p of inclusion in the
highest density region.</dd>
<dt>gridsize</dt>
<dd>the number of equally spaced points used for binned kernel
density estimation.</dd>
<dt>nMChdr</dt>
<dd>the size of the Monte Carlo sample used for density quantile
approximation of the highest density region, as described in Hyndman (1996).</dd>
<dt>graphProgress</dt>
<dd>logical flag: if `TRUE' then plots showing the progress
of the bandwidth selection algorithm are produced.</dd></dl>

Arguments

Author

Highest Density Region Bandwidth — hdrbw

<dl>

<dt>x</dt>
<dd>Numerical vector containing data.</dd>


<dt>HDRlevel</dt>
<dd>HDR-level as defined in Hyndman (1996). Setting `HDRlevel'
equal to p (0&lt;p&lt;1) corresponds to a probability of 1-p of inclusion in the
highest density region.</dd>


<dt>gridsize</dt>
<dd>the number of equally spaced points used for binned kernel
density estimation.</dd>


<dt>nMChdr</dt>
<dd>the size of the Monte Carlo sample used for density quantile
approximation of the highest density region, as described in Hyndman (1996).</dd>


<dt>graphProgress</dt>
<dd>logical flag: if `TRUE' then plots showing the progress
of the bandwidth selection algorithm are produced.</dd>

</dl>

hdrbw: Highest Density Region Bandwidth

Description

Usage

Value

Arguments

Author

Details

References

Examples