Analyzes and models data subject to sampling biases.
    Provides functions to estimate the density and cumulative distribution
    functions from biased samples of continuous distributions. Includes
    the estimators proposed by Bhattacharyya et al. (1988)
    <doi:10.1080/03610928808829825> and Jones (1991) <doi:10.2307/2337020>
    for density, and by Cox (2005, ISBN:052184939X) and Bose and Dutta
    (2022) <doi:10.1007/s00184-021-00824-3> for distribution, with
    different bandwidth selectors. Also includes a real length-biased
    dataset on shrub width from Muttlak (1988)
    <https://www.proquest.com/openview/3dd74592e623cdbcfa6176e85bd3d390/1?cbl=18750&diss=y&pq-origsite=gscholar>.

Search and download data from over 40 databases hosted by the World Bank, including the World Development Indicators ('WDI'), International Debt Statistics, Doing Business, Human Capital Index, and Sub-national Poverty indicators.

Provides functions to calculate the Water Deficit Index (WDI) and 
    the Evaporative Fraction (EF) using geospatial raster data such as fractional 
    vegetation cover (FVC) and surface-air temperature difference (TS-TA). 
    The package automates regression-based edge fitting and produces continuous 
    spatial maps of surface moisture and evaporative dynamics.

Provides a workflow for exploring World Development Indicators (WDI) country-level panel data. It downloads WDI data using the 'WDI' package and computes diagnostic indices that capture the temporal behaviour of the data by incorporating the grouping structure of the data. The set of diagnostic indices implemented includes variation features, trend and shape features, and sequential temporal features. This method is described in Akinfenwa, Cahill, and Hurley (2025) "'wdiexplorer': An R package Designed for Exploratory Analysis of World Development Indicators (WDI) Data" <doi:10.48550/arXiv.2511.07027>. We adapt the clustering diagnostics and visualisation methodology described in Rousseeuw (1987) <doi:10.1016/0377-0427(87)90125-7> and selected time series features from Hyndman and Athanasopoulos (2021) "Forecasting: Principles and Practice" <https://otexts.com/fpp3/>.