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bugs-fundamentals

Teach BUGS/JAGS modeling with precision parameterization and R integration.

9|1|Updated Jan 10, 2026
Search Tags:#modeling#bugs#mcmc#bayesian#jags#r-integration
One-click install
npx skills add https://github.com/choxos/BiostatAgent --skill bugs-fundamentals
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bugs-fundamentals
Source: https://github.com/choxos/BiostatAgent/tree/main/plugins/bayesian-modeling/skills/bugs-fundamentals
Command: npx skills add https://github.com/choxos/BiostatAgent --skill bugs-fundamentals

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides foundational knowledge for writing BUGS/JAGS models, ensuring correct precision handling, declarative syntax, and reliable integration with R.

Core Features & Use Cases

  • Writing new BUGS/JAGS models
  • Understanding precision parameterization and syntax
  • Converting between BUGS/JAGS and Stan
  • Integrating with R via R2jags or R2WinBUGS

Quick Start

Create a minimal BUGS model file and run it in R with R2jags to fit a simple normal data example.

Frequently Asked Questions about bugs-fundamentals

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I write a BUGS model in R using R2jags?▼

Precision parameterization in BUGS and JAGS defines distributions using precision instead of variance, where precision equals the inverse of variance. Correctly specifying precision ensures proper prior distribution scaling and reliable Bayesian modeling results.

What is precision parameterization in BUGS and JAGS?▼

Precision parameterization in BUGS and JAGS defines distributions using precision instead of variance, where precision equals the inverse of variance. Correctly specifying precision ensures proper prior distribution scaling and reliable Bayesian modeling results.

Can I convert BUGS models to Stan syntax?▼

Understanding model blocks, priors, and R2jags or R2WinBUGS interfaces is required before using BUGS for Bayesian modeling. You also need familiarity with declarative syntax and precision parameterization to ensure correct specification and reproducible results.

Do I need to know R2WinBUGS interfaces to use JAGS for Bayesian modeling?▼

Understanding model blocks, priors, and R2jags or R2WinBUGS interfaces is required before using BUGS for Bayesian modeling. You also need familiarity with declarative syntax and precision parameterization to ensure correct specification and reproducible results.

How does declarative syntax work in JAGS probabilistic programming?▼

Declarative syntax in JAGS probabilistic programming specifies the probabilistic graphical model relationships rather than sequential execution steps. Writing model blocks with distributions and priors allows the MCMC sampler to infer the posterior distribution correctly.

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