我深深致力於開源軟件，並在15年多的時間裡一直在構建專業級工具——可以追溯到 Google Code 時代。我的工作將嚴格的統計方法與現代軟件工程實踐相結合，包括版本控制（Git/GitHub）、持續集成、代理 AI、容器技術和敏捷方法。我領導科學軟件開發團隊交付高性能、可靠且用戶友好的工具，這些工具被研究人員和從業者廣泛採用。我的大部分工作是用 C++ 構建的，為 R 和 Python 提供包裝器，針對高性能計算環境進行優化。在所有項目中，我在設計時都考慮到性能和可用性，確保複雜的方法既可擴展又易於訪問。
近年來，我也將 AI 融入工作，推動研發與創新（一些示例見此處）。
重點項目包括：
epiworld 框架是一個用 C++ 編寫的高級基於代理的建模框架，專為流行病學建模的快速原型設計而設計。該庫可在 R、Python 以及 shiny 包中使用。
epiworld 最值得注意的應用是對美國近期麻疹爆發的建模。您可以在此處查看開發的 shiny 應用程序版本。 
rgexf 包。創建、讀取和寫入 ‘GEXF’（圖形交換 ‘XML’ 格式）圖形文件（用於 ‘Gephi’ 等）。使用 ‘XML’ 包，rgexf 允許讀取和寫入 GEXF 文件，包括屬性、‘GEXF’ 可視化屬性（如顏色、大小和位置）、網絡動態（節點和邊）以及邊的權重。用戶可以逐元素或通過數據框大量構建/處理圖形，通過 ‘gexf-js’（一個 ‘javascript’ 庫）在網頁瀏覽器上可視化圖形，並與 ‘igraph’ 包交互。
您可以在此處查看 gexf-js 庫的實際應用版本。
ergmito R 包。使用精確統計量對小型網絡的指數隨機圖模型（ERGMs）進行模擬和估計，如 Vega Yon 等人（2020）所示 https://doi.org/10.1016/j.socnet.2020.07.005。與 ‘ergm’ 包不同，‘ergmito’ 避免使用馬爾可夫鏈最大似然估計器（MC-MLE），而是使用最大似然估計器（MLE）來擬合小型網絡的 ERGMs。由於對小型網絡來說詳盡枚舉在計算上是可行的，因此這個 R 包利用了這一點，並提供了直接計算似然函數和其他相關函數的工具，這意味著在許多情況下，小型網絡的 ERGMs 估計和模擬都可以比基於模擬的算法更快、更準確。
以下是我構建或貢獻的軟件包的詳盡列表。您可以在 我的 GitHub 上查看我最近的貢獻和正在進行的開源項目
引用数据来自 OpenAlex，下载量来自 CRAN。更新于 2026-08-15。
软件包活跃2026
Build, Import and Export GEXF Graph Files
Vega Yon, G. G.
CRAN0.17.0downloads653kstars32被引用5
networksvisualizationdata formats
CRAN•Docs•Repo•DOI
简介
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 and 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.
Analysis of Diffusion and Contagion Processes on Networks
Vega Yon, G. G., & Valente, T.
CRAN1.25.0downloads58kstars92
networksdiffusion
CRAN•Docs•Repo•DOI
简介
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), Valente (1995), Myers (2000), Iyengar and others (2011), Burt (1987), among others.
Statistical Inference of Annotated Phylogenetic Trees
Vega Yon, G. G.
CRAN0.3-6downloads19kstars6被引用1
phylogeneticsbayesiangenomics
CRAN•Repo•DOI
简介
Implements a parsimonious evolutionary model to analyze and predict gene-functional annotations in phylogenetic trees, as described in Vega Yon et al. (2021). 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 tools for visualization of annotated phylogenies, calculation of posterior probabilities (prediction), and goodness-of-fit assessment.
Beautiful graph drawing
Vega Yon, G. G.
CRAN0.4-0downloads22kstars53
networksvisualization
CRAN•Docs•Repo•DOI
简介
A graph visualization engine that emphasizes aesthetics while providing default parameters that yield out-of-the-box, nice visualizations. The package is built on top of 'The Grid Graphics Package' and works seamlessly with 'igraph' and 'network' objects.
your to-go motif accountant
Vega Yon, G. G.
CRAN0.2.2downloads2.5k
networksstatistical models
CRAN•Docs•Repo•DOI
简介
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, it offers an efficient distribution system for CRAN, avoiding replication of this code across the sources of other packages. This package follows the same approach as the 'BH' package, which provides 'Boost' headers for R packages.
Estimation and simulation of Multi-binary response models
Vega Yon, G. G.
CRAN0.2.1.0downloads2.8kstars1
statistical modelsnetworks
CRAN•Docs•Repo•DOI
简介
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, implementing the models described in Vega Yon, Valente, and Pugh (2023). DEFMs include Exponential-Family Random Graph Models (ERGMs), which characterize graphs using sufficient statistics, also the core of DEFMs. Using sufficient statistics, the package describes data through meaningful motifs, such as transitions between different states and the joint distribution of the outcomes.
Fast Agent-Based Epi Models
Meyer, D., & Vega Yon, G. G.
CRAN0.14.0.0downloads15kstars14被引用2
epidemiologyagent-based models
CRAN•Docs•Repo•DOI
简介
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. 'epiworldR' is ideal for simulation studies featuring large populations.
Analyze Outbreak Models of Multi-Group Populations with Vaccination
Toth, D., Wagoner, J., Ray, W., & Vega Yon, G. G.
version0.1.1stars2
epidemiology
Link•Docs•Repo
简介
Models infectious disease dynamics in populations with multiple subgroups having different vaccination rates, transmission characteristics, and contact patterns. Calculates final and intermediate outbreak sizes, forms age-structured contact models with automatic fetching of U.S. census data, and explores vaccination scenarios with an interactive 'shiny' dashboard for a model with two subgroups, as described in Nguyen et al. (2024) and Duong et al. (2026).
Measles Epidemiological Models
Vega Yon, G. G.
CRAN0.2.0downloads2.2kstars4
epidemiologyagent-based models
CRAN•Repo•DOI
简介
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, making it ideal for studying measles outbreaks, vaccination strategies, and intervention policies.
Fast and Effortless Calibration of Agent-Based Models using Machine Learning
Najafzadehkhoei, S., Vega Yon, G. G., & Modenesi, B.
CRAN0.1.4downloads1.3kstars1
epidemiologyagent-based modelsmachine learning
CRAN•Docs•Repo•DOI
简介
Provides tools and pre-trained Machine Learning (ML) models for calibration of Agent-Based Models (ABMs) built with the R package 'epiworldR', implementing methods described in Najafzadehkhoei, Vega Yon, Modenesi, and Meyer (2025). Users can automatically calibrate ABMs in seconds with pre-trained ML models, effectively focusing on simulation rather than calibration, bridging a gap that allows public health practitioners to run their own ABMs without the advanced technical expertise often required by calibration.
Tools for Studying Imaginary Cognitive Social Structure
Najafzadehkhoei, S., Vega Yon, G. G., & Tanaka, K.
CRAN0.1.0downloads2.3kstars1被引用3
networkscognition
CRAN•Docs•Repo•DOI
简介
Tools for measuring and testing imaginary cognitive social structure (CSS) motifs — patterns of false positives and negatives in cognitively perceived social networks relative to the actual network, categorized as partially false, completely false, and mixed false imaginary motifs, as described in Tanaka and Vega Yon (2024).
Agent-Based Modeling of Measles in US cities hosting the 2026 FIFA World Cup
Vega Yon, G. G.
epidemiologyagent-based modelsvisualization
Link•Repo
简介
Agent-based measles outbreak simulations across the 11 major U.S. cities hosting the 2026 FIFA World Cup. Built on the 'epiworldR' and 'measles' R packages, and using census-derived age structure and MMR vaccination coverage, the project provides baseline scenario dashboards summarizing simulated outbreak size over time and the probability that outbreaks exceed given case-count thresholds for each host city. With large international crowds expected, the dashboard supports public-health preparedness by helping to understand measles transmission risk around the tournament.
AI-powered Dashboard to Explore the InsighNet community
Vega Yon, G. G.
text analysis
Link•Repo
简介
An AI-powered dashboard exploring the InsightNet research community: academic profiles and publications for researchers affiliated with InsightNet's centers. A scheduled pipeline collects papers and preprints from ORCID, Europe PMC, PubMed, arXiv, medRxiv/bioRxiv, and Crossref, and daily activity from public web pages, RSS/Atom, Bluesky, and GitHub, normalizing it into a static snapshot. The standalone site includes an AI-assisted expert-finder that answers questions from the collected publications and profiles, citing the underlying record, a browser-side keyword search, and a browsable, filterable publication list, with no runtime server or frontend dependencies.
软件包活跃2025
Exponential Random Graph Models for Small Networks
Vega Yon, G. G., & de la Haye, K.
CRAN0.3-2downloads28kstars9被引用47
networksstatistical models
CRAN•Docs•Repo•DOI
简介
Simulation and estimation of Exponential Random Graph Models (ERGMs) for small networks using exact statistics, as shown in Vega Yon et al. (2020). As a difference from the 'ergm' package, 'ergmito' circumvents using a Markov-Chain Maximum Likelihood Estimator (MC-MLE) and instead uses a 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.
Shiny interface for epiworldR
Meyer, D., & Vega Yon, G. G.
CRAN0.2.3downloads14kstars3
epidemiologyagent-based modelsvisualization
CRAN•Docs•Repo•DOI
简介
R 'shiny' web apps for epidemiological Agent-Based Models. It provides a user-friendly interface to the Agent-Based Modeling (ABM) R package 'epiworldR', with support for the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Recovered (SIR), and Susceptible-Exposed-Infected-Recovered (SEIR) models. 'epiworldRShiny' provides a web-based user interface for running various epidemiological ABMs, simulating interventions, and visualizing results interactively.
A Package for Bayesian Renewal Modeling with JAX and NumPyro
Bayer, D., Morris, D. H., Vega Yon, G. G., Martin, T., & Bidari, S.
version0.1.0stars29
epidemiologybayesian
Link•Repo
简介
A flexible tool for simulation and statistical inference of epidemiological models, emphasizing hierarchical multi-signal renewal models. Built on top of the 'numpyro' Python library, 'PyRenew' provides core components for model building. A renewal model estimates new infections from recent past infections using a generation interval, from which it infers the time-varying reproduction number R(t). PyRenew's strength lies in multi-signal integration for pooling information across diverse observed data streams, such as hospital admissions, wastewater concentrations, and emergency department visits, each with distinct observation delays, noise characteristics, and spatial resolutions.
Jointly infers infection dynamics from wastewater data and epidemiological indicators
Johnson, K., Morris, D., Abbott, S., Bernal Zelaya, C., Vega Yon, G. G., Bayer, D., Magee, A., & Olesen, S.
version0.1.1.99stars31
epidemiologybayesian
Link•Repo
简介
An implementation of a hierarchical semi-mechanistic renewal approach jointly calibrating to multiple wastewater concentration datasets from subsets of a specified population and epidemiological indicators, such as cases or hospital admissions, from the whole population. The framework extends the widely used semi-mechanistic renewal framework 'EpiNow2', using a Bayesian latent variable approach implemented in the probabilistic programming language 'Stan'. The package fits these two data sources and produces estimated and forecasted hospital admissions, estimated and forecasted wastewater concentrations, and global and local R(t) estimates for the subpopulations represented by each wastewater catchment area.
A Lightweight Wrapper for 'Slurm'
Vega Yon, G. G.
CRAN0.5-4downloads37kstars61被引用3
hpcparallel computing
CRAN•Repo•DOI
简介
'Slurm', Simple Linux Utility for Resource Management, 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.
A friendly MCMC framework
Vega Yon, G. G.
CRAN0.5-2downloads35kstars16被引用8
bayesianmcmc
CRAN•Repo•DOI
简介
Provides a friendly (flexible) Markov Chain Monte Carlo (MCMC) framework for implementing the Metropolis-Hastings algorithm in a modular way, allowing users to specify an automatic convergence checker, personalized transition kernels, and out-of-the-box multiple MCMC chains using parallel computing. Among the methods included are Haario (2001) Adaptive Metropolis, Vihola (2012) Robust Adaptive Metropolis, and Thawornwattana et al. (2018) Mirror transition kernels.
库活跃2022
A Flexible and General Agent Based Model Engine
Vega Yon, G. G.
version0.0-1stars10
epidemiologyagent-based modelshpc
Link•Repo
简介
A general framework for epidemiologic simulation implemented as a header-only 'C++' template library. The core principle of 'epiworld' is fast epidemiological prototyping for building complex models quickly: models can have an arbitrary set of states, viruses and tools (e.g., vaccines, mask-wearing) can be designed with arbitrary features, and multiple tools and viruses can coexist in the same simulation. It depends only on the standard library and is capable of over 150 million person-day simulations per second.
Implementing the Felsenstein's Tree Pruning algorithm
Vega Yon, G. G.
version0.0-1stars1
phylogeneticsalgorithms
Link•Repo
简介
A C++ template library implementing Felsenstein's tree-pruning algorithm for efficiently computing likelihood functions on phylogenies. The library reads a tree object as a list of source-target dyads (edges) and allows users to store arbitrary arguments via memory pointers and 'std::function' callbacks invoked with those arguments and the tree structure data. Trees are stored as offspring and parent lists, accessible through a 'TreeIterator' class implementing pre- and post-order traversals for pruning.
Stata Module for Parallel Computing
Vega Yon, G. G., & Quistorff, B.
version1.20.0stars134
hpcparallel computing
Link•Repo
简介
A Stata module for parallel computing. By organizing a job into several Stata instances, parallel provides out-of-the-box parallel computing for faster simulations, bootstrapping, reshaping big data, and more, without requiring any knowledge of parallel computing or a Stata/MP license. Depending on the number of available processors, parallel has shown to dramatically speed up computations, sometimes outperforming Stata/MP itself.
Working with Google's 'Public Data Explorer' DSPL Metadata Files
Vega Yon, G. G.
CRAN0.16.1downloads62kstars8
data formats
CRAN•Repo•DOI
简介
Provides a collection of functions to set up 'Google Public Data Explorer' data visualization tool with your own data, building automatically the corresponding DataSet Publishing Language file, or DSPL (XML), metadata file jointly with the CSV files. All zip-up and ready to be published in 'Public Data Explorer'.
Implementation of Artificial Bee Colony (ABC) Optimization
Vega Yon, G. G., & Muñoz, E.
CRAN0.15.0downloads94kstars32
optimization
CRAN•Repo•DOI
简介
An implementation of Karaboga's (2005) Artificial Bee Colony Optimization algorithm. This was developed upon the basic version programmed in C and available at the algorithm's official website.
Out-of-the-box analysis and reporting tools for twitter
Vega Yon, G. G.
version0.16stars38
text analysisnetworks
Link•Repo•DOI
简介
A set of tools to download, process, and analyze tweets, including methods for exporting the outputs through 'D3js'.
没有符合这些筛选条件的项目。
本網站版本使用 GitHub Copilot 從原始英文版本自動翻譯，尚未經過人工驗證。
