Projection Pursuit (PP) algorithm for dimension reduction based on Gaussian Mixture Models (GMMs) for density estimation using Genetic Algorithms (GAs) to maximise an approximated negentropy index. For more details see Scrucca and Serafini (2019) <doi:10.1080/10618600.2019.1598871>.

The Poverty Probability Index (PPI) is a poverty measurement tool 
    for organizations and businesses with a mission to serve the poor. The PPI 
    is statistically-sound, yet simple to use: the answers to 10 questions about 
    a household’s characteristics and asset ownership are scored to compute the 
    likelihood that the household is living below the poverty line – or above by 
    only a narrow margin. This package contains country-specific lookup data tables
    used as reference to determine the poverty likelihood of a household based
    on their score from the country-specific PPI questionnaire. These lookup 
    tables have been extracted from documentation of the PPI found at 
    <https://www.povertyindex.org> and managed by Innovations for Poverty Action 
    <https://poverty-action.org/>.

We provide new tools for the identification of prognostic and predictive biomarkers. For further details we refer the reader to the paper: Zhu et al. Identification of prognostic and predictive biomarkers in high-dimensional data with PPLasso. BMC Bioinformatics. 2023 Jan 23;24(1):25.

Implements data processing described in <doi:10.1126/sciadv.abk3283> to align modern differentially private data with formatting of older US Census data releases. The primary goal is to read in Census Privacy Protected Microdata Files data in a reproducible way. This includes tools for aggregating to relevant levels of geography by creating geographic identifiers which match the US Census Bureau's numbering. Additionally, there are tools for grouping race numeric identifiers into categories, consistent with OMB (Office of Management and Budget) classifications. Functions exist for downloading and linking to existing sources of privacy protected microdata.