select_kernel

internal

Analyse species-habitat associations in R. Therefore, information about the location
of the species (as a point pattern) is needed together with environmental conditions
(as a categorical raster). To test for significance habitat associations, one of
the two components is randomized. Methods are mainly based on Plotkin et al. (2000)
<doi:10.1006/jtbi.2000.2158> and Harms et al. (2001) <doi:10.1111/j.1365-2745.2001.00615.x>.

Maximillian H.K. Hesselbarth

shar

Species-Habitat Associations

Maximilian H.K. Hesselbarth

Marco Sciaini

Chris Wudel

Zeke Marshall

Thomas Etherington

Janosch Heinermann

select_kernel function

<dl><dt>kernel_arg</dt>
<dd>Parameter of the function
reconstruct_pattern_multi_trait_marks, specifies the kernel to be used to
calculate the energy, possible kernels can be: Gaussian, Epanechnikov,
Rectangular, Cumulative.</dd>
<dt>bw</dt>
<dd>Bandwidth with which the kernels are scaled, so that this is the
standard deviation of the smoothing kernel.</dd>
<dt>rmax</dt>
<dd>Maximum distance at which the summary statistics are evaluated.</dd>
<dt>divisor</dt>
<dd>Divisor in the smoothing kernel, d or r.</dd></dl>

Arguments

select_kernel — select_kernel

<dl>

<dt>kernel_arg</dt>
<dd>Parameter of the function
reconstruct_pattern_multi_trait_marks, specifies the kernel to be used to
calculate the energy, possible kernels can be: Gaussian, Epanechnikov,
Rectangular, Cumulative.</dd>


<dt>bw</dt>
<dd>Bandwidth with which the kernels are scaled, so that this is the
standard deviation of the smoothing kernel.</dd>


<dt>rmax</dt>
<dd>Maximum distance at which the summary statistics are evaluated.</dd>


<dt>divisor</dt>
<dd>Divisor in the smoothing kernel, d or r.</dd>

</dl>

select_kernel: select_kernel

Description

Usage

Value

Arguments

Details