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CosmoSIS cosmological parameter estimation skill for MCMC sampling and likelihood analysis
--- name: cosmosis-parameter-estimator-48e40ab1f508 description: CosmoSIS cosmological parameter estimation skill for MCMC sampling and likelihood analysis allowed-tools: - Bash - Read - Write - Edit - Glob - Grep metadata: specialization: physics domain: science category: cosmology phase: 6 graph: domains: [domain:physics] skillAreas: [skill-area:physics-simulation, skill-area:statistical-analysis, skill-area:mathematical-reasoning] workflows: [workflow:experiment-design, workflow:peer-review-cycle] roles: [role:research-scientist, role:computational-scientist] --- # CosmoSIS Parameter Estimator ## Purpose Provides expert guidance on CosmoSIS for cosmological parameter estimation, including modular likelihood construction and MCMC sampling. ## Capabilities - Modular likelihood construction - Multiple sampler support (emcee, multinest, polychord) - Prior specification - Chain analysis and diagnostics - Plotting and visualization - Pipeline construction ## Usage Guidelines 1. **Pipeline Setup**: Configure modular analysis pipeline 2. **Likelihoods**: Build likelihood functions from data 3. **Priors**: Specify parameter priors 4. **Sampling**: Run MCMC with appropriate sampler 5. **Analysis**: Analyze chains and compute posteriors ## Tools/Libraries - CosmoSIS - emcee - GetDist--- name: cosmosis-parameter-estimator-48e40ab1f508 description: CosmoSIS cosmological parameter estimation skill for MCMC sampling and likelihood analysis allowed-tools: - Bash - Read - Write - Edit - Glob - Grep metadata: specialization: physics domain: science category: cosmology phase: 6 graph: domains: [domain:physics] skillAreas: [skill-area:physics-simulation, skill-area:statistical-analysis, skill-area:mathematical-reasoning] workflows: [workflow:experiment-design, workflow:peer-review-cycle] roles: [role:research-scientist, role:computational-scientist] --- # CosmoSIS Parameter Estimator ## Purpose Provides expert guidance on CosmoSIS for cosmological parameter estimation, including modular likelihood construction and MCMC sampling. ## Capabilities - Modular likelihood construction - Multiple sampler support (emcee, multinest, polychord) - Prior specification - Chain analysis and diagnostics - Plotting and visualization - Pipeline construction ## Usage Guidelines 1. **Pipeline Setup**: Configure modular analysis pipeline 2. **Likelihoods**: Build likelihood functions from data 3. **Priors**: Specify parameter priors 4. **Sampling**: Run MCMC with appropriate sampler 5. **Analysis**: Analyze chains and compute posteriors ## Tools/Libraries - CosmoSIS - emcee - GetDist
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.