mcmc-sampling-stan - Letta Skills
Description
Guide for performing Markov Chain Monte Carlo (MCMC) sampling using RStan or PyStan. This skill should be used when implementing Bayesian statistical models, fitting hierarchical models, working with Stan modeling language, or running MCMC diagnostics. Applies to tasks involving posterior sampling, Bayesian inference, and probabilistic programming with Stan.
Type
Skill
Ecosystem
Cross-platform
Trust Score
86%
Related Skills
Stable Diffusion WebUI
Feature-rich web interface for Stable Diffusion image generation by AUTOMATIC1111.
LangChain
Comprehensive framework for building LLM-powered applications with chains, agents, and retrieval.
LobeChat
Modern, extensible AI chat framework with plugin ecosystem and multi-model support.
Open WebUI
Self-hosted web UI for LLMs with multi-model support, RAG, and plugin system.