An implementation of split-population duration regression models. 
    Unlike regular duration models, split-population duration models are
    mixture models that accommodate the presence of a sub-population that is 
    not at risk for failure, e.g. cancer patients who have been cured by 
    treatment. This package implements Weibull and Loglogistic forms for the 
    duration component, and focuses on data with time-varying covariates. 
    These models were originally formulated in Boag (1949) and Berkson and Gage 
    (1952), and extended in Schmidt and Witte (1989).

A spatio-dynamic modelling package that focuses on three
    characteristic wetland plant communities in a semiarid Mediterranean
    wetland in response to hydrological pressures from the catchment. The
    package includes the data on watershed hydrological pressure and the
    initial raster maps of plant communities but also allows for random initial
    distribution of plant communities. For more detailed info see: Martinez-Lopez et al. (2015) <doi:10.1016/j.ecolmodel.2014.11.024>.

A graph community detection algorithm that aims to be performant
    on large graphs and robust, returning consistent results across runs.
    SpeakEasy 2 (SE2), the underlying algorithm, is described in Chris Gaiteri,
    David R. Connell & Faraz A. Sultan et al. (2023)
    <doi:10.1186/s13059-023-03062-0>. The core algorithm is written in 'C',
    providing speed and keeping the memory requirements low. This implementation
    can take advantage of multiple computing cores without increasing memory
    usage. SE2 can detect community structure across scales, making it a good
    choice for biological data, which often has hierarchical structure. Graphs
    can be passed to the algorithm as adjacency matrices using base 'R'
    matrices, the 'Matrix' library, 'igraph' graphs, or any data that can be
    coerced into a matrix.

It allows running 'Praat' scripts from R and it provides some
    wrappers for basic plotting. It also adds support for literate markdown
    tangling. The package is designed to bring reproducible phonetic research
    into R.