epiworldR - Fast Agent-Based Epi Models
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.
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abmagent-based-modelingcovid-19epidemicsepidemiologyr-programmingrpackrpkgseirseir-modelsimulationsirsir-modelquartocppopenmp
9.40 score 11 stars 2 dependents 135 scripts 648 downloadsnetdiffuseR - Analysis of Diffusion and Contagion Processes on Networks
Empirical statistical analysis, visualization and simulation of diffusion and contagion processes on networks. The package implements algorithms for calculating network diffusion statistics such as transmission rate, hazard rates, exposure models, network threshold levels, infectiousness (contagion), and susceptibility. The package is inspired by work published in Valente, et al., (2015) <DOI:10.1016/j.socscimed.2015.10.001>; Valente (1995) <ISBN: 9781881303213>, Myers (2000) <DOI:10.1086/303110>, Iyengar and others (2011) <DOI:10.1287/mksc.1100.0566>, Burt (1987) <DOI:10.1086/228667>; among others.
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contagiondiffusion-networknetwork-analysisnetwork-visualizationopenblascppopenmp
8.98 score 91 stars 211 scripts 778 downloads
slurmR - A Lightweight Wrapper for 'Slurm'
'Slurm', Simple Linux Utility for Resource Management <https://slurm.schedmd.com/>, is a popular 'Linux' based software used to schedule jobs in 'HPC' (High Performance Computing) clusters. This R package provides a specialized lightweight wrapper of 'Slurm' with a syntax similar to that found in the 'parallel' R package. The package also includes a method for creating socket cluster objects spanning multiple nodes that can be used with the 'parallel' package.
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bioinformaticshpcslurm
7.63 score 61 stars 232 scripts 277 downloads
fmcmc - A friendly MCMC framework
Provides a friendly (flexible) Markov Chain Monte Carlo (MCMC) framework for implementing Metropolis-Hastings algorithm in a modular way allowing users to specify automatic convergence checker, personalized transition kernels, and out-of-the-box multiple MCMC chains using parallel computing. Most of the methods implemented in this package can be found in Brooks et al. (2011, ISBN 9781420079425). Among the methods included, we have: Haario (2001) <doi:10.1007/s11222-011-9269-5> Adaptive Metropolis, Vihola (2012) <doi:10.1007/s11222-011-9269-5> Robust Adaptive Metropolis, and Thawornwattana et al. (2018) <doi:10.1214/17-BA1084> Mirror transition kernels.
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adaptivebayesian-inferencemarkov-chain-monte-carlomcmcmetropolis-hastingsparallel-computing
7.22 score 16 stars 1 dependents 58 scripts 319 downloads
rgexf - Build, Import, and Export GEXF Graph Files
Create, read, and write 'GEXF' (Graph Exchange 'XML' Format) graph files (used in 'Gephi' and others). Using the 'XML' package, rgexf allows reading and writing GEXF files, including attributes, 'GEXF' visual attributes (such as color, size, and position), network dynamics (for both edges and nodes), and edges' weights. Users can build/handle graphs element-by-element or massively through data frames, visualize the graph on a web browser through 'gexf-js' (a 'javascript' library), and interact with the 'igraph' package.
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gephigexfgexf-graph-filessocial-networkxml
7.11 score 30 stars 214 scripts 951 downloadsnetplot - Beautiful Graph Drawing
A graph visualization engine that emphasizes on aesthetics at the same time providing default parameters that yield out-of-the-box-nice visualizations. The package is built on top of 'The Grid Graphics Package' and seamlessly work with 'igraph' and 'network' objects.
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graph-visualizationigraphnetscinetwork-analysisnetwork-visualizationsnastatnet
6.66 score 53 stars 86 scripts 272 downloads
aphylo - Statistical Inference and Prediction of Annotations in Phylogenetic Trees
Implements a parsimonious evolutionary model to analyze and predict gene-functional annotations in phylogenetic trees as described in Vega Yon et al. (2021) <doi:10.1371/journal.pcbi.1007948>. Focusing on computational efficiency, 'aphylo' makes it possible to estimate pooled phylogenetic models, including thousands (hundreds) of annotations (trees) in the same run. The package also provides the tools for visualization of annotated phylogenies, calculation of posterior probabilities (prediction) and goodness-of-fit assessment featured in Vega Yon et al. (2021).
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annotationsinferencephylogeneticsrcpparmadillocpp
6.49 score 6 stars 104 scripts 646 downloads
measles - Measles Epidemiological Models
A specialized collection of measles epidemiological models built on the 'epiworldR' framework. This package is a spinoff from 'epiworldR' focusing specifically on measles transmission dynamics. It includes models for school settings with quarantine and isolation policies, mixing models with population groups, and risk-based quarantine strategies. The models use Agent-Based Models (ABM) with a fast 'C++' backend from the 'epiworld' library. Ideal for studying measles outbreaks, vaccination strategies, and intervention policies.
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abmagent-based-modelingepidemiologyindividual-based-modellingmeaslesmeasles-mumps-rubella-vacciner-programmingsimulationquartocpp
6.25 score 2 stars 10 scripts 484 downloads
ergmito - Exponential Random Graph Models for Small Networks
Simulation and estimation of Exponential Random Graph Models (ERGMs) for small networks using exact statistics as shown in Vega Yon et al. (2020) <DOI:10.1016/j.socnet.2020.07.005>. As a difference from the 'ergm' package, 'ergmito' circumvents using Markov-Chain Maximum Likelihood Estimator (MC-MLE) and instead uses Maximum Likelihood Estimator (MLE) to fit ERGMs for small networks. As exhaustive enumeration is computationally feasible for small networks, this R package takes advantage of this and provides tools for calculating likelihood functions, and other relevant functions, directly, meaning that in many cases both estimation and simulation of ERGMs for small networks can be faster and more accurate than simulation-based algorithms.
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ergmexponential-random-graph-modelsstatisticsopenblascppopenmp
5.50 score 9 stars 35 scripts 246 downloads
ABCoptim - Implementation of Artificial Bee Colony (ABC) Optimization
An implementation of Karaboga (2005) Artificial Bee Colony Optimization algorithm <http://mf.erciyes.edu.tr/abc/pub/tr06_2005.pdf>. This was developed upon the basic version programmed in C and available at the algorithm's official website.
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artificial-bee-colonyoptimizationr-programmingrcppstochastic-optimizerscpp
4.65 score 31 stars 29 scripts 844 downloads
barry - Your Go-to Motif Accountant
Provides the 'C++' header-only library 'barry' for use in R packages. 'barry' is a 'C++' template library for counting sufficient statistics on binary arrays and building discrete exponential-family models. It provides tools for sparse arrays, user-defined count statistics, support set constraints, power set generation, and includes modules for Discrete Exponential Family Models (DEFMs) and network statistics. By placing these headers in this package, we offer an efficient distribution system for CRAN as replication of this code in the sources of other packages is avoided. This package follows the same approach as the 'BH' package which provides 'Boost' headers for R packages.
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motifsr-libraryr-programmingstatistics
3.95 score 2 dependents 274 downloadsimaginarycss - Tools for Studying Imaginary Cognitive Social Structure
This package provides functions to measure and test imaginary cognitive social structure (CSS) motifs, which are patterns of perceived relationships among individuals in a social network. The package includes tools for calculating motif frequencies, comparing observed motifs to expected distributions, and visualizing motif structures. It implements the methods described in Tanaka and Vega Yon (2023) <DOI:10.1016/j.socnet.2023.11.005>.
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cognitive-social-structurescsssnasocial-network-analysisquartocpp
3.78 score 1 stars 15 scripts 488 downloads
defm - Estimation and Simulation of Multi-Binary Response Models
Multi-binary response models are a class of models that allow for the estimation of multiple binary outcomes simultaneously. This package provides functions to estimate and simulate these models using the Discrete Exponential-Family Models [DEFM] framework. In it, we implement the models described in Vega Yon, Valente, and Pugh (2023) <doi:10.48550/arXiv.2211.00627>. DEFMs include Exponential-Family Random Graph Models [ERGMs], which characterize graphs using sufficient statistics, which is also the core of DEFMs. Using sufficient statistics, we can describe the data through meaningful motifs, for example, transitions between different states, joint distribution of the outcomes, etc.
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ergmmlemodelingsimulationstatisticscppopenmp
3.48 score 1 stars 4 scripts 128 downloads