Prompt
Check a dataset before analysis
Find missing values, inconsistent formats, duplicates, and questions that could invalidate results.
ClaudeChatGPTGeminiData & Analytics
Dave AI
MCMC Diagnostics
MCMC convergence diagnostics and analysis
instructions.md
--- name: mcmc-diagnostics-4554bc5c2eba description: MCMC convergence diagnostics and analysis allowed-tools: - Bash - Read - Write - Edit - Glob - Grep metadata: specialization: mathematics domain: science category: statistical-computing phase: 6 graph: domains: [domain:mathematics] specializations: [specialization:computational-mathematics] skillAreas: [skill-area:statistical-analysis, skill-area:mathematical-reasoning, skill-area:data-analysis] workflows: [workflow:experiment-design] roles: [role:research-scientist, role:data-scientist] --- # MCMC Diagnostics ## Purpose Provides MCMC convergence diagnostics and analysis capabilities for validating Bayesian inference results. ## Capabilities - Rhat (potential scale reduction) computation - Effective sample size (ESS) calculation - Trace plot generation - Autocorrelation analysis - Divergence detection - Energy diagnostic (E-BFMI) ## Usage Guidelines 1. **Convergence Check**: Verify Rhat < 1.01 for all parameters 2. **Sample Quality**: Ensure ESS is sufficient for inference 3. **Visual Inspection**: Review trace plots for mixing 4. **Divergences**: Address divergent transitions ## Tools/Libraries - ArviZ - CODA - MCMCpack--- name: mcmc-diagnostics-4554bc5c2eba description: MCMC convergence diagnostics and analysis allowed-tools: - Bash - Read - Write - Edit - Glob - Grep metadata: specialization: mathematics domain: science category: statistical-computing phase: 6 graph: domains: [domain:mathematics] specializations: [specialization:computational-mathematics] skillAreas: [skill-area:statistical-analysis, skill-area:mathematical-reasoning, skill-area:data-analysis] workflows: [workflow:experiment-design] roles: [role:research-scientist, role:data-scientist] --- # MCMC Diagnostics ## Purpose Provides MCMC convergence diagnostics and analysis capabilities for validating Bayesian inference results. ## Capabilities - Rhat (potential scale reduction) computation - Effective sample size (ESS) calculation - Trace plot generation - Autocorrelation analysis - Divergence detection - Energy diagnostic (E-BFMI) ## Usage Guidelines 1. **Convergence Check**: Verify Rhat < 1.01 for all parameters 2. **Sample Quality**: Ensure ESS is sufficient for inference 3. **Visual Inspection**: Review trace plots for mixing 4. **Divergences**: Address divergent transitions ## Tools/Libraries - ArviZ - CODA - MCMCpack
Platform guidance
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.