Processes data from Molecular Dynamics simulations using 
    Self Organising Maps. Features include the ability to read different 
    input formats. Trajectories can be analysed to identify groups of important
    frames. Output visualisation can be generated for maps and pathways.
    Methodological details can be found in Motta S et al (2022) 
    <doi:10.1021/acs.jctc.1c01163>.
    I/O functions for xtc format files were implemented using the 'xdrfile'
    library available under open source license. The relevant information can 
    be found in inst/COPYRIGHT.

Structural multivariate-univariate linear mixed model solver for estimation of multiple random effects with unknown variance-covariance structures (e.g., heterogeneous and unstructured) and known covariance among levels of random effects (e.g., pedigree and genomic relationship matrices) (Covarrubias-Pazaran, 2016 <doi:10.1371/journal.pone.0156744>; Maier et al., 2015 <doi:10.1016/j.ajhg.2014.12.006>; Jensen et al., 1997). REML estimates can be obtained using the Direct-Inversion Newton-Raphson and Direct-Inversion Average Information algorithms for the problems r x r (r being the number of records) or using the Henderson-based average information algorithm for the problem c x c (c being the number of coefficients to estimate). Spatial models can also be fitted using the two-dimensional spline functionality available.

Integrates the 13C nuclear magnetic resonance spectra using different integration ranges. Output depends on the method chosen. For the Molecular Mixing Model, a measurement of the fitting quality is given by its R-factor. For more details see: <doi:10.5281/zenodo.10137768>.

Formulas for calculating sound velocity, water pressure, depth, 
    density, absorption and sonar equations.

Simulates the cultural evolution of quantitative traits of bird song. 'SongEvo' is an individual- (agent-) based model. 'SongEvo' is spatially-explicit and can be parameterized with, and tested against, measured song data. Functions are available for model implementation, sensitivity analyses, parameter optimization, model validation, and hypothesis testing.