time-series-models

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Bayesian time-series modeling in Stan and JAGS.

Authorchoxos
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Bayesian time-series modeling provides probabilistic forecasts and uncertainty estimates for sequential data, enabling better decision making in dynamic contexts.

Core Features & Use Cases

  • AR, MA, ARMA, and state-space models implemented in Stan and JAGS for flexible forecasting.
  • Tools for model specification, diagnostics, and comparison of competing time-series structures.
  • Use cases include forecasting demand, anomaly detection, and nowcasting in finance, engineering, epidemiology, and environmental monitoring.

Quick Start

Provide your time-series data and run the included Stan or JAGS workflows to fit AR/MA/ARMA/state-space models.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: time-series-models
Download link: https://github.com/choxos/BiostatAgent/archive/main.zip#time-series-models

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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