weight.IC

An implementation of IC weighting that first calulates the difference in IC values by subtracting all values from the lowest IC value. Second, the changes are expoentiated divided by a sum of the same and exponentiated yet again.

Perform multivariate modeling of evolved traits, with special attention to
understanding the interplay of the multi-factorial determinants of their origins
in complex ecological settings (Stephens, 2007 <doi:10.1016/j.tree.2006.12.003>).
This software primarily concentrates on phylogenetic regression analysis, enabling
implementation of tree transformation averaging and visualization functionality.
Functions additionally support information theoretic approaches
(Grueber, 2011 <doi:10.1111/j.1420-9101.2010.02210.x>;
Garamszegi, 2011 <doi:10.1007/s00265-010-1028-7>)
such as model averaging and selection of phylogenetic models.
Accessory functions are also implemented for coef standardization (Cade 2015),
selection uncertainty, and variable importance (Burnham & Anderson 2000).
There are other numerous functions for visualizing confounded variables,
plotting phylogenetic trees, as well as reporting and exporting modeling results.
Lastly, as challenges to ecology are inherently multifarious, and therefore often
multi-dataset, this package features several functions to support the identification,
interpolation, merging, and updating of missing data and outdated nomenclature.

David Schruth

mmodely

Modeling Multivariate Origins Determinants - Evolutionary
Lineages in Ecology

weight.IC function

<dl><dt>IC</dt>
<dd>a vector of IC values</dd></dl>

Arguments

Get IC weights — weight.IC

<dl>

<dt>IC</dt>
<dd>a vector of IC values</dd>

</dl>

weight.IC: Get IC weights

Description

Usage

Value

Arguments

Examples