Based on Natural Earth <https://www.naturalearthdata.com/>, a subset of countries can
             easily be selected with their administrative boundaries, joined with an external
	     data frame and plotted as a thematic map.

A simple function for easier package loading and auto-installation.

Subsampling methods for big data under different models and assumptions.
    Starting with linear regression and leading to Generalised Linear Models, softmax
    regression, and quantile regression. Specifically, the model-robust subsampling method 
    proposed in Mahendran, A., Thompson, H., and McGree, J. M. (2023) <doi:10.1007/s00362-023-01446-9>, 
    where multiple models can describe the big data, and the subsampling framework for potentially 
    misspecified Generalised Linear Models in Mahendran, A., Thompson, H., and McGree, J. M. (2025)
    <doi:10.48550/arXiv.2510.05902>.

Methods to reduce confounding bias from unmeasured confounders in observational studies of vaccine efficacy using negative control outcomes.

The Negative Binomial regression with mean and shape modeling and mean and variance modeling and Beta Binomial regression with mean and dispersion modeling.

Estimating the number of essential genes in a genome on
    the basis of data from a random transposon mutagenesis experiment,
    through the use of a Gibbs sampler.
    Lamichhane et al. (2003) <doi:10.1073/pnas.1231432100>.

Researchers often want to evaluate whether there is a negligible
    relationship among variables. The 'negligible' package provides functions that 
    are useful for conducting negligible effect testing (also called
    equivalence testing). For example, there are functions for evaluating the 
    equivalence of means or the presence of a negligible association 
    (correlation or  regression). Beribisky, N., Mara, C., & Cribbie, R. A. (2020) <doi:10.20982/tqmp.16.4.p424>.
    Beribisky, N., Davidson, H., Cribbie, R. A. (2019) <doi:10.7717/peerj.6853>.
    Shiskina, T., Farmus, L., & Cribbie, R. A. (2018) <doi:10.20982/tqmp.14.3.p167>.
    Mara, C. & Cribbie, R. A. (2017) <doi:10.1080/00220973.2017.1301356>.
    Counsell, A. & Cribbie, R. A. (2015) <doi:10.1111/bmsp.12045>.
    van Wieringen, K. & Cribbie, R. A. (2014) <doi:10.1111/bmsp.12015>.
    Goertzen, J. R. & Cribbie, R. A. (2010) <doi:10.1348/000711009x475853>.
    Cribbie, R. A., Gruman, J. & Arpin-Cribbie, C. (2004) <doi:10.1002/jclp.10217>.