mean_dist

This function generates the mean pairwise distance matrix from a set
many pairwise distance matrices. Note: all matrices should be of the same dimension.

Computational infrastructure for biogeography, community ecology,
and biodiversity conservation (Daru et al. 2020) <doi:10.1111/2041-210X.13478>.
It is based on the methods described in Daru et al. (2020) <doi:10.1038/s41467-020-15921-6>.
The original conceptual work is described in Daru et al. (2017) <doi:10.1016/j.tree.2017.08.013>
on patterns and processes of biogeographical regionalization. Additionally, the package
contains fast and efficient functions to compute more standard conservation measures
such as phylogenetic diversity, phylogenetic endemism, evolutionary distinctiveness
and global endangerment, as well as compositional turnover (e.g., beta diversity).

Barnabas H. Daru

phyloregion

Biogeographic Regionalization and Macroecology

Piyal Karunarathne

Klaus Schliep

Xiaobei Zhao

Albin Sandelin

Luciano Pataro

mean_dist function

<dl><dt>files</dt>
<dd>list of pairwise distance matrices stored as CSVs or .rds
with the same dimensions.</dd>
<dt>trace</dt>
<dd>Trace the function; trace = 2 or higher will be more voluminous.</dd>
<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd></dl>

Arguments

Mean distance matrix from a set of distance matrices — mean_dist

<dl>

<dt>files</dt>
<dd>list of pairwise distance matrices stored as CSVs or .rds
with the same dimensions.</dd>


<dt>trace</dt>
<dd>Trace the function; trace = 2 or higher will be more voluminous.</dd>


<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd>

</dl>

mean_dist: Mean distance matrix from a set of distance matrices

Description

Usage

Value

Arguments