Provides helper functions, metadata utilities, and workflows for 
    administering and managing databases on the 'Motherduck' cloud platform. 
    Some features require a 'Motherduck' account (<https://motherduck.com/>).

Describes spatial patterns of categorical raster data for 
    any defined regular and irregular areas. 
    Patterns are described quantitatively using built-in signatures 
    based on co-occurrence matrices but also allows for 
    any user-defined functions. 
    It enables spatial analysis such as search, change detection,
    and clustering to be performed on spatial patterns (Nowosad (2021) <doi:10.1007/s10980-020-01135-0>).

Tools for spectral clustering of weighted directed networks using motif
    adjacency matrices. Methods perform well on large and sparse networks, and
    random sampling methods for generating weighted directed networks are also
    provided. Based on methodology detailed in Underwood, Elliott and Cucuringu
    (2020) <arXiv:2004.01293>.

Tools for motif analysis in multi-level networks.
    Multi-level networks combine multiple networks in one, e.g.
    social-ecological networks. Motifs are small configurations of nodes
    and edges (subgraphs) occurring in networks. 'motifr' can visualize
    multi-level networks, count multi-level network motifs and compare
    motif occurrences to baseline models. It also identifies contributions
    of existing or potential edges to motifs to find critical or missing
    edges. The package is in many parts an R wrapper for the excellent
    'SESMotifAnalyser' 'Python' package written by Tim Seppelt.

Functions for fitting models of trait evolution
        on phylogenies for continuous traits. The majority of functions are
        described in Thomas and Freckleton (2012)
        <doi:10.1111/j.2041-210X.2011.00132.x> and allow tests of variation 
        in the rates of trait evolution.

The temporal relationship between motor neurons can offer 
    explanations for neural strategies. We combined functions to reduce neuron 
    action potential discharge data and analyze it for short-term, time-domain 
    synchronization. Even more so, motoRneuron combines most available methods 
    for the determining cross correlation histogram peaks and most available 
    indices for calculating synchronization into simple functions. See 
    Nordstrom, Fuglevand, and Enoka (1992) <doi:10.1113/jphysiol.1992.sp019244> 
    for a more thorough introduction.