A set of functions for applying a 
    restricted linear algebra to the analysis of 
    count-based data. See the accompanying preprint
    manuscript: "Normalizing need not be the norm:
    count-based math for analyzing single-cell data"
    Church et al (2022) <doi:10.1101/2022.06.01.494334>
    This tool is specifically designed to analyze 
    count matrices from single cell RNA sequencing 
    assays. The tools implement several count-based
    approaches for standard steps in single-cell 
    RNA-seq analysis, including scoring genes and cells, 
    comparing cells and clustering, calculating differential 
    gene expression, and several methods for rank 
    reduction. There are many opportunities for further
    optimization that may prove useful in the analysis of
    other data. We provide the source code freely
    available at <https://github.com/shchurch/countland>
    and encourage users and developers to fork the code for 
    their own purposes.

Calculates metrics of proportionality using the logit-normal multinomial model.  It can also provide empirical and plugin estimates of these metrics.

Flexible univariate count models based on renewal processes. The
    models may include covariates and can be specified with familiar formula
    syntax as in glm() and package 'flexsurv'.  The methodology is described by
    Kharrat et all (2019) <doi:10.18637/jss.v090.i13> (included as vignette
    'Countr_guide' in the package).

Wrangle country data more effectively and quickly. 
    This package contains functions to easily identify and convert country names,
    download country information, merge country data from different sources, 
    and make quick world maps.

Standardize country names, convert them into one of 40
    different coding schemes, convert between coding schemes, and assign
    region descriptors.

Modeling under- and over-dispersed count data using extended Poisson process models as in the article Faddy and Smith (2011) <doi:10.18637/jss.v069.i06> .