Use three methods to estimate parameters from a mediation analysis
  with a binary misclassified mediator. These methods correct for the problem
  of "label switching" using Youden's J criteria. A detailed description of the 
  analysis methods is available in Webb and Wells (2024), "Effect estimation in 
  the presence of a misclassified binary mediator" <doi:10.48550/arXiv.2407.06970>.

Provides the "comma-free call" operator: '%(%'. Use it to call a
    function without commas between the arguments. Just replace the '('
    with '%(%' in a function call, supply your arguments as standard R
    expressions enclosed by '{ }', and be free of commas (for that call).

Autosimilarity curves, standardization of spatial extent, dissimilarity indexes that overweight rare species, phylogenetic and functional (pairwise and multisample) dissimilarity indexes and nestedness for phylogenetic, functional and other diversity metrics. The methods for phylogenetic and functional nestedness is described in Melo, Cianciaruso and Almeida-Neto (2014) <doi:10.1111/2041-210X.12185>. This should be a complement to available packages, particularly 'vegan'.

Provides a framework for modeling relationships between functional traits and both quantitative and qualitative environmental variables at the community level. It includes tools for trait binning, likelihood-based environmental estimation, model evaluation, fossil projection into modern ecometric space, and result visualization. For more details see Vermillion et al. (2018) <doi:10.1007/978-3-319-94265-0_17>, Polly et al. (2011) <doi:10.1098/rspb.2010.2233> and Polly and Head (2015) <doi:10.1017/S1089332600002953>.

Analysis of network community objects with applications to neuroimaging data. There are two main components to this package. The first is the hierarchical multimodal spinglass (HMS) algorithm, which is a novel community detection algorithm specifically tailored to the unique issues within brain connectivity. The other is a suite of semiparametric kernel machine methods that allow for statistical inference to be performed to test for potential associations between these community structures and an outcome of interest (binary or continuous).