Tools to simulate realistic raw case data for an epidemic in
    the form of line lists and contacts using a branching process.
    Simulated outbreaks are parameterised with epidemiological parameters
    and can have age-structured populations, age-stratified
    hospitalisation and death risk and time-varying case fatality risk.

Simulate genotypes in SNP (single nucleotide polymorphisms) Matrix as random numbers from an uniform distribution, for diploid organisms (coded by 0, 1, 2), Sikorska et al., (2013) <doi:10.1186/1471-2105-14-166>, or half-sib/full-sib SNP matrix from real or simulated parents SNP data, assuming mendelian segregation. Simulate phenotypic traits for real or simulated SNP data, controlled by a specific number of quantitative trait loci  and their effects, sampled from a Normal or an Uniform distributions, assuming a pure additive model. This is useful for testing association and genomic prediction models or for educational purposes.

Simulation tools for planning Vitamin D studies. Individual vitamin D status 
             profiles are simulated, modelling population heterogeneity in trial arms. 
             Exposures to infectious agents are generated, with infection depending on vitamin D status.

The sinaplot is a data visualization chart suitable for plotting
    any single variable in a multiclass data set. It is an enhanced jitter strip
    chart, where the width of the jitter is controlled by the density
    distribution of the data within each class.

Implementation of the Conditional Least Square (CLS) estimates and
    its covariance matrix for the first-order spatial integer-valued
    autoregressive model (SINAR(1,1)) proposed by Ghodsi (2012)
    <doi:10.1080/03610926.2011.560739>.

This implements the Brunton et al (2016; PNAS <doi:10.1073/pnas.1517384113>) sparse
    identification algorithm for finding ordinary differential equations for a measured 
    system from raw data (SINDy). The package includes a set of additional tools for 
    working with raw data, with an emphasis on cognitive science applications (Dale 
    and Bhat, 2018 <doi:10.1016/j.cogsys.2018.06.020>). See 
    <https://github.com/racdale/sindyr> for examples and updates.