Provides the ability to perform "Marginal Mediation"--mediation
   wherein the indirect and direct effects are in terms of the average marginal effects 
   (Bartus, 2005, <https://EconPapers.repec.org/RePEc:tsj:stataj:v:5:y:2005:i:3:p:309-329>). 
   The style of the average marginal effects stems from Thomas Leeper's work on the "margins" package.
   This framework allows the use of categorical mediators and outcomes with little change in interpretation
   from the continuous mediators/outcomes. See <doi:10.13140/RG.2.2.18465.92001> for more details 
   on the method.

Estimation of relative risks, risk differences, and 
  partial effects from mixed model. Marginalisation over random effect terms is accomplished using Markov Chain Monte Carlo.

An R port of the margins command from 'Stata', which can be used to
    calculate marginal (or partial) effects from model objects.

Create marimekko (mosaic) plots as a 'ggplot2' layer.
    Column widths encode marginal proportions of one categorical variable
    and segment heights encode conditional proportions of a second
    categorical variable.

Simulates Blockchain-Enabled Maritime Transportation Systems 
    (BMTS) by integrating asynchronous, great-circle vessel kinematics with 
    decentralised edge-computing consensus layers. The package provides a fully 
    self-contained cyber-range running completely offline, permitting the 
    risk-free injection of spatial and telemetry threat vectors (e.g., geofence 
    breaches, coordinate modification, and node impersonation). It includes an 
    interactive workspace engine built using 'shinydashboard' and 'leaflet' map 
    layers for monitoring vessel states and ledger updates. Implemented 
    consensus structures are modeled on a lightweight Proof-of-Authentication 
    framework optimized for resource-constrained distributed nodes.

Implementation of the Marine Predators Algorithm (MPA) in R. MPA is a
    nature-inspired optimization algorithm that follows the rules governing optimal
    foraging strategy and encounter rate policy between predator and prey in marine
    ecosystems. Based on the paper by Faramarzi et al. (2020)
    <doi:10.1016/j.eswa.2020.113377>.