Advanced Stochastics
CommunityAdvance stochastic theory with simulations.
AuthorDevelata
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides hands-on tools and guidance to study advanced stochastic topics, combining theory and computational experiments to illuminate complex behaviors in random matrices, large deviations, and stochastic processes.
Core Features & Use Cases
- Random Matrix Theory: simulate eigenvalues of large symmetric matrices and compare with the semicircle law.
- Large Deviations: visualize concentration phenomena and rate functions via sample means.
- Stochastic Processes: explore Markov chains, Brownian motion, martingales, and Poisson processes with guided experiments.
- Reproducible Research: use Python scripts to reproduce plots and results for teaching, research, or self-study.
Quick Start
Run the included scripts to generate RMT eigenvalue plots and LDP simulations for exponential/ Bernoulli distributions.
Dependency Matrix
Required Modules
numpyscipymatplotlib
Components
scripts
💻 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: Advanced Stochastics Download link: https://github.com/Develata/Deve-Skills/archive/main.zip#advanced-stochastics Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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