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.

Manage package documentation and namespaces from the command line. 
             Programmatically attach namespaces in R and Rmd script, populates 
             'Roxygen2' skeletons with information scraped from within functions and 
             populate the Imports field of the DESCRIPTION file.

When comparing single cases to control populations and no parameters are known researchers and clinicians must estimate these with a control sample. This is often done when testing a case's abnormality on some variable or testing abnormality of the discrepancy between two variables. Appropriate frequentist and Bayesian methods for doing this are here implemented, including tests allowing for the inclusion of covariates. These have been developed first and foremost by John Crawford and Paul Garthwaite, e.g. in Crawford and Howell (1998) <doi:10.1076/clin.12.4.482.7241>, Crawford and Garthwaite (2005) <doi:10.1037/0894-4105.19.3.318>, Crawford and Garthwaite (2007) <doi:10.1080/02643290701290146> and Crawford, Garthwaite and Ryan (2011) <doi:10.1016/j.cortex.2011.02.017>. The package is also equipped with power calculators for each method.