A collection of robust statistical methods based on Wilcox' WRS functions. It implements robust t-tests (independent and dependent samples), robust ANOVA (including between-within subject designs), quantile ANOVA, robust correlation, robust mediation, and nonparametric ANCOVA models based on robust location measures.

A collection of implementations of classical and
    novel algorithms for weighted sampling without replacement.
    Implementations include the algorithm of Efraimidis and Spirakis (2006)
    <doi:10.1016/j.ipl.2005.11.003> and Wong and Easton (1980)
    <doi:10.1137/0209009>.

An adaptation for estuaries (tidal waters) of weighted regression
    on time, discharge, and season to evaluate trends in water quality time series. 
    Please see Beck and Hagy (2015) <doi:10.1007/s10666-015-9452-8> for 
    details.

Top-Down mass spectrometry aims to identify entire proteins as well as their (post-translational) modifications or ions bound (eg Chen et al (2018) <doi:10.1021/acs.analchem.7b04747>). 
    The pattern of internal fragments (Haverland et al (2017) <doi:10.1007/s13361-017-1635-x>) may reveal important information about the original structure of the proteins studied 
    (Skinner et al (2018) <doi:10.1038/nchembio.2515> and Li et al (2018) <doi:10.1038/nchem.2908>). 
    However, the number of possible internal fragments gets huge with longer proteins and subsequent identification of internal fragments remains challenging, 
    in particular since the the accuracy of measurements with current mass spectrometers represents a limiting factor.   
    This package attempts to deal with the complexity of internal fragments and allows identification of terminal and internal fragments from deconvoluted mass-spectrometry data.

Predicts individual race/ethnicity using surname, first name,
    middle name, geolocation, and other attributes, such as gender and
    age. The method utilizes Bayes' Rule (with optional measurement error
    correction) to compute the posterior probability of each racial
    category for any given individual. The package implements methods
    described in Imai and Khanna (2016) "Improving Ecological Inference by
    Predicting Individual Ethnicity from Voter Registration Records"
    Political Analysis <DOI:10.1093/pan/mpw001> and Imai, Olivella, and
    Rosenman (2022) "Addressing census data problems in race imputation
    via fully Bayesian Improved Surname Geocoding and name supplements"
    <DOI:10.1126/sciadv.adc9824>.  The package also incorporates the data
    described in Rosenman, Olivella, and Imai (2023) "Race and ethnicity
    data for first, middle, and surnames"
    <DOI:10.1038/s41597-023-02202-2>.