Constructing an epistemic model such that, for every player i and for every choice c(i) which is optimal, there is one type that expresses common belief in rationality.

Builds contingency tables that cross-tabulate multiple 
    categorical variables and also calculates various summary measures.
    Export to a variety of formats is supported, including: 'HTML', 
    'LaTeX', and 'Excel'.

Provides functions to test for gene x gene interactions in a
    bi-parental population of inbred lines. The data are fitted with the
    mixed linear model described in Rio et al. (2022) <doi:10.1101/2022.12.18.520958>, 
    that accounts for gene x gene interactions
    at both the fixed effect and variance levels. The package also
    provides graphical tools to display the gene x gene interaction trend at
    the mean level and the variance component analysis.

Tools for training and practicing epidemiologists including methods for two-way and multi-way contingency tables.

A collection of small functions useful for epidemics analysis and infectious disease modelling. This includes computation of basic reproduction numbers from growth rates, generation of hashed labels to anonymize data, and fitting discretized Gamma distributions.

It allows you to automatically monitor trends of tweets by time, place and topic aiming at detecting public health threats early through the detection of signals (e.g. an unusual increase in the number of tweets). It was designed to focus on infectious diseases, and it can be extended to all hazards or other fields of study by modifying the topics and keywords. More information is available in the 'epitweetr' peer-review publication (doi:10.2807/1560-7917.ES.2022.27.39.2200177).

A flexible framework for Agent-Based Models (ABM), the 'epiworldR' package provides methods for prototyping disease outbreaks and transmission models using a 'C++' backend, making it very fast. It supports multiple epidemiological models, including the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Removed (SIR), Susceptible-Exposed-Infected-Removed (SEIR), and others, involving arbitrary mitigation policies and multiple-disease models. Users can specify infectiousness/susceptibility rates as a function of agents' features, providing great complexity for the model dynamics. Furthermore, 'epiworldR' is ideal for simulation studies featuring large populations.