plot.kdensity

lines.kdensity

points.kdensity

The <code>plot</code> method for <code>kdensity</code> objects.

Handles univariate non-parametric density estimation with
parametric starts and asymmetric kernels in a simple and flexible way.
Kernel density estimation with parametric starts involves fitting a
parametric density to the data before making a correction with kernel
density estimation, see Hjort & Glad (1995) <doi:10.1214/aos/1176324627>.
Asymmetric kernels make kernel density estimation more efficient on bounded
intervals such as (0, 1) and the positive half-line. Supported asymmetric
kernels are the gamma kernel of Chen (2000) <doi:10.1023/A:1004165218295>,
the beta kernel of Chen (1999) <doi:10.1016/S0167-9473(99)00010-9>, and the
copula kernel of Jones & Henderson (2007) <doi:10.1093/biomet/asm068>.
User-supplied kernels, parametric starts, and bandwidths are supported.

Jonas Moss

kdensity

Kernel Density Estimation with Parametric Starts and Asymmetric
Kernels

Martin Tveten

plot.kdensity function

<dl><dt>x</dt>
<dd>a <code>kdensity</code> object.</dd>
<dt>range</dt>
<dd>range of x values.</dd>
<dt>plot_start</dt>
<dd>logical; if <code>TRUE</code>, plots the parametric start instead of the kernel density estimate.</dd>
<dt>zero_line</dt>
<dd>logical; if <code>TRUE</code>, add a base line at <code>y = 0</code>.</dd>
<dt>...</dt>
<dd>further plotting parameters.</dd></dl>

Arguments

Plot, Lines and Points Methods for Kernel Density Estimation — plot.kdensity

<dl>

<dt>x</dt>
<dd>a <code>kdensity</code> object.</dd>


<dt>range</dt>
<dd>range of x values.</dd>


<dt>plot_start</dt>
<dd>logical; if <code>TRUE</code>, plots the parametric start instead of the kernel density estimate.</dd>


<dt>zero_line</dt>
<dd>logical; if <code>TRUE</code>, add a base line at <code>y = 0</code>.</dd>


<dt>...</dt>
<dd>further plotting parameters.</dd>

</dl>

plot.kdensity: Plot, Lines and Points Methods for Kernel Density Estimation

Description

Usage

Value

Arguments

See Also

Examples