monte-carlo-simulation
// Monte Carlo methods for uncertainty quantification
$ git log --oneline --stat
stars:384
forks:73
updated:March 4, 2026
SKILL.mdreadonly
SKILL.md Frontmatter
namemonte-carlo-simulation
descriptionMonte Carlo methods for uncertainty quantification
allowed-toolsBash,Read,Write,Edit,Glob,Grep
metadata[object Object]
Monte Carlo Simulation
Purpose
Provides Monte Carlo methods for uncertainty quantification, integration, and probabilistic analysis.
Capabilities
- Standard Monte Carlo sampling
- Importance sampling
- Stratified sampling
- Quasi-Monte Carlo (Sobol, Halton sequences)
- Markov chain Monte Carlo
- Convergence analysis
Usage Guidelines
- Sampling Strategy: Choose appropriate sampling method
- Sample Size: Determine sufficient sample sizes
- Variance Reduction: Apply variance reduction techniques
- Convergence: Monitor convergence diagnostics
Tools/Libraries
- NumPy
- scipy.stats
- SALib