Provides methods for retrieving United States Geological Survey (USGS) water data using sequential and parallel processing (Bengtsson, 2022 <doi:10.32614/RJ-2021-048>). In addition to parallel methods, data wrangling and additional statistical attributes are provided.

This is a small, lightweight package that lets users investigate the distribution of genotypes in genotype-by-sequencing (GBS) data where they expect (by and large) Hardy-Weinberg equilibrium, in order to assess rates of genotyping errors and the dependence of those rates on read depth.  It implements a Markov chain Monte Carlo (MCMC) sampler using 'Rcpp' to compute a Bayesian estimate of what we call the heterozygote miscall rate for restriction-associated digest (RAD) sequencing data and other types of reduced representation GBS data. It also provides functions to generate plots of expected and observed genotype frequencies. Some background on these topics can be found in a recent paper "Recent advances in conservation and population genomics data analysis" by Hendricks et al. (2018) <doi:10.1111/eva.12659>, and another paper describing the MCMC approach is in preparation with Gordon Luikart and Thierry Gosselin.

Look up the username and full name of the current user,
    the current user's email address and 'GitHub' username,
    using various sources of system and configuration information.

The Model Disability Survey (MDS) <https://www.who.int/activities/collection-of-data-on-disability> is a World Health Organization (WHO) general population survey
    instrument to assess the distribution of disability within a country or 
    region, grounded in the International Classification of Functioning, 
    Disability and Health <https://www.who.int/standards/classifications/international-classification-of-functioning-disability-and-health>. This package provides fit-for-purpose functions 
    for calculating and presenting the results from this survey, as used by 
    the WHO. The package primarily provides functions for implementing
    Rasch Analysis (see Andrich (2011) <doi:10.1586/erp.11.59>) to
    calculate a metric scale for disability.