get_kernel_start_support

This function takes the supplied values of kernel, start, and support
and fills in the non-supplied ones. It also handles inconsistencies,
such as providing a support on (-Inf, Inf) but a kernel on (0, Inf).

internal

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

get_kernel_start_support function

<dl><dt>kernel</dt>
<dd>Supplied kernel; string or list.</dd>
<dt>start</dt>
<dd>Supplied parametric start; string or list.</dd>
<dt>support</dt>
<dd>Binary vector.</dd></dl>

Arguments

Fill in missing kernel, start or support given the supplied values. — get_kernel_start_support

<dl>

<dt>kernel</dt>
<dd>Supplied kernel; string or list.</dd>


<dt>start</dt>
<dd>Supplied parametric start; string or list.</dd>


<dt>support</dt>
<dd>Binary vector.</dd>

</dl>

get_kernel_start_support: Fill in missing kernel, start or support given the supplied values.

Description

Usage

Value

Arguments

Details