Provides easy access to essential climate change datasets to non-climate experts. Users can download the latest raw data from authoritative sources and view it via pre-defined 'ggplot2' charts. Datasets include atmospheric CO2, methane, emissions, instrumental and proxy temperature records, sea levels, Arctic/Antarctic sea-ice, Hurricanes, and Paleoclimate data. Sources include: NOAA Mauna Loa Laboratory <https://gml.noaa.gov/ccgg/trends/data.html>, Global Carbon Project <https://www.globalcarbonproject.org/carbonbudget/>, NASA GISTEMP <https://data.giss.nasa.gov/gistemp/>, National Snow and Sea Ice Data Center <https://nsidc.org/home>, CSIRO <https://research.csiro.au/slrwavescoast/sea-level/measurements-and-data/sea-level-data/>, NOAA Laboratory for Satellite Altimetry <https://www.star.nesdis.noaa.gov/socd/lsa/SeaLevelRise/> and HURDAT Atlantic Hurricane Database <https://www.aoml.noaa.gov/hrd/hurdat/Data_Storm.html>, Vostok Paleo carbon dioxide and temperature data: <doi:10.3334/CDIAC/ATG.009>.

Built by Hodges lab members for current and future Hodges lab members. Other individuals are welcome to use as well. Provides useful functions that the lab uses everyday to analyze various genomic datasets. Critically, only general use functions are provided; functions specific to a given technique are reserved for a separate package. As the lab grows, we expect to continue adding functions to the package to build on previous lab members code.

Higher order likelihood inference is a promising approach for
    analyzing small sample size data. The 'holi' package provides web applications
    for higher order likelihood inference. It currently supports linear, logistic,
    and Poisson generalized linear models through the rstar_glm() function, based
    on Pierce and Bellio (2017) <doi:10.1111/insr.12232> and 'likelihoodAsy'.
    The package offers two main features: LA_rstar(), which launches an interactive
    'shiny' application allowing users to fit models with rstar_glm() through their
    web browser, and sim_rstar_glm_pgsql(), which streamlines the process of
    launching a web-based 'shiny' simulation application that saves results to a
    user-created 'PostgreSQL' database.