Download and read US Census Bureau data relationship files. Provides 
    support for cleaning and using block assignment files since 2010, as described in 
    <https://www.census.gov/geographies/reference-files/time-series/geo/block-assignment-files.html>. 
    Also includes support for working with block equivalency files, used for years 
    outside of decennial census years.

Waffle plots are rectangular pie charts that represent a quantity or abundances using
    colored squares or other symbol. This makes them better at transmitting information as the
    discrete number of squares is easier to read than the circular area of pie charts.
    While the original waffle charts were rectangular with 10 rows and columns, with a single square
    representing 1%, they are nowadays popular in various infographics to visualize any
    proportional ratios.

Fast Bayesian estimation and forecasting of age-specific
    rates, probabilities, and means, based on 'Template Model Builder'.

Bagged OutlierTrees is an explainable unsupervised outlier detection method based on an ensemble implementation of the existing OutlierTree procedure (Cortes, 2020). This implementation takes advantage of bootstrap aggregating (bagging) to improve robustness by reducing the possible masking effect and subsequent high variance (similarly to Isolation Forest), hence the name "Bagged OutlierTrees". To learn more about the base procedure OutlierTree (Cortes, 2020), please refer to <arXiv:2001.00636>.

Bagging bandwidth selection methods for the Parzen-Rosenblatt and Nadaraya-Watson estimators. These 
  bandwidth selectors can achieve greater statistical precision than their non-bagged counterparts while being 
    computationally fast. See Barreiro-Ures et al. (2020) <doi:10.1093/biomet/asaa092> and 
  Barreiro-Ures et al. (2021) <doi:10.48550/arXiv.2105.04134>.

Running and comparing meta-analyses of data with hierarchical 
    Bayesian models in Stan, including convenience functions for formatting
    data, plotting and pooling measures specific to meta-analysis. This implements many models
    from Meager (2019) <doi:10.1257/app.20170299>.