A collection of fast and flexible functions for analyzing
    omics data in observational studies. Multiple different approaches for
    integrating multiple environmental/genetic factors, omics data, and/or
    phenotype data are implemented. This includes functions for performing
    omics wide association studies with one or more variables of interest
    as the exposure or outcome; a function for performing a meet in the
    middle analysis for linking exposures, omics, and outcomes (as
    described by Chadeau-Hyam et al., (2010)
    <doi:10.3109/1354750X.2010.533285>); and a function for performing a
    mixtures analysis across all omics features using quantile-based
    g-Computation (as described by Keil et al., (2019)
    <doi:10.1289/EHP5838>).

Classes and helper functions for loading, extracting, converting, 
    manipulating, plotting and aggregating epidemiological parameters for infectious diseases. 
    Epidemiological parameters extracted from the literature are loaded from the 'epiparameterDB'
    R package.

A data package containing a database of epidemiological
    parameters. It stores the data for the 'epiparameter' R package.
    Epidemiological parameter estimates are extracted from the literature.

A toolbox to make it easy to analyze plant disease epidemics. It
    provides a common framework for plant disease intensity data recorded over
    time and/or space. Implemented statistical methods are currently mainly
    focused on spatial pattern analysis (e.g., aggregation indices, Taylor and
    binary power laws, distribution fitting, SADIE and 'mapcomp' methods). See
    Laurence V. Madden, Gareth Hughes, Franck van den Bosch (2007)
    <doi:10.1094/9780890545058> for further information on these methods.
    Several data sets that were mainly published in plant disease epidemiology
    literature are also included in this package.

Provides functions for estimating plant pathogen parameters from
    access period (AP) experiments. Separate functions are implemented for
    semi-persistently transmitted (SPT) and persistently transmitted (PT)
    pathogens. The common AP experiment exposes insect cohorts to infected source
    plants, healthy test plants, and intermediate plants (for PT pathogens). The
    package allows estimation of acquisition and inoculation rates during feeding,
    recovery rates, and latent progression rates (for PT pathogens). Additional
    functions support inference of epidemic risk from pathogen and local
    parameters, and also simulate AP experiment data. The functions implement
    probability models for epidemiological analysis, as derived in Donnelly et
    al. (2025), <doi:10.32942/X29K9P>. These models were originally
    implemented in the 'EpiPv' 'GitHub' package.