pnp_rangebagging

This function both fits rangebagging models Drake2015-sbS4DM and projects those distributions to new covariates.

internal

Implements a set of distribution modeling methods that are suited to species with small sample sizes (e.g., poorly sampled species or rare species). While these methods can also be used on well-sampled taxa, they are united by the fact that they can be utilized with relatively few data points. More details on the currently implemented methodologies can be found in Drake and Richards (2018) <doi:10.1002/ecs2.2373>, Drake (2015) <doi:10.1098/rsif.2015.0086>, and Drake (2014) <doi:10.1890/ES13-00202.1>.

Brian S. Maitner

S4DM

Small Sample Size Species Distribution Modeling

Robert L. Richards

Ben S. Carlson

John M. Drake

Cory Merow

pnp_rangebagging function

<dl><dt>data</dt>
<dd>dataframe of covariates</dd>
<dt>method</dt>
<dd>one of either "fit" or "predict"</dd>
<dt>object</dt>
<dd>fitted object returned by a pnp_... function. Only needed when method = "predict"</dd>
<dt>v</dt>
<dd>Integer. Number of votes to use in the aggregation, default is 100.</dd>
<dt>d</dt>
<dd>Integer. Number of dimensions (i.e. covariates) to use in aggregations, default is 2.</dd>
<dt>p</dt>
<dd>Numeric. Fraction of observations (i.e. occurrences) to use in each replicate aggregation. Default is 0.5</dd></dl>

Arguments

Internal function for rangebagging in plug-and-play SDMs. — pnp_rangebagging

<dl>

<dt>data</dt>
<dd>dataframe of covariates</dd>


<dt>method</dt>
<dd>one of either "fit" or "predict"</dd>


<dt>object</dt>
<dd>fitted object returned by a pnp_... function. Only needed when method = "predict"</dd>


<dt>v</dt>
<dd>Integer. Number of votes to use in the aggregation, default is 100.</dd>


<dt>d</dt>
<dd>Integer. Number of dimensions (i.e. covariates) to use in aggregations, default is 2.</dd>


<dt>p</dt>
<dd>Numeric. Fraction of observations (i.e. occurrences) to use in each replicate aggregation. Default is 0.5</dd>

</dl>

pnp_rangebagging: Internal function for rangebagging in plug-and-play SDMs.

Description

Usage

Arguments

Details

References