Module stochastic 

Stochastic processes module for Proof Engine.

Provides Brownian motion, geometric Brownian motion, Ornstein-Uhlenbeck, Poisson processes, Markov chains, Monte Carlo simulation, random matrix theory, stochastic differential equations, Lévy flights, and percolation.

Re-exports

pub use brownian::BrownianMotion;

pub use brownian::BrownianMotion2D;

pub use brownian::BrownianBridge;

pub use brownian::BrownianRenderer;

pub use brownian::Rng;

pub use geometric_bm::GeometricBM;

pub use geometric_bm::GBMRenderer;

pub use ornstein_uhlenbeck::OrnsteinUhlenbeck;

pub use ornstein_uhlenbeck::OURenderer;

pub use poisson::PoissonProcess;

pub use poisson::NonHomogeneousPoisson;

pub use poisson::CompoundPoisson;

pub use markov::MarkovChain;

pub use markov::ContinuousTimeMarkov;

pub use markov::MarkovChainRenderer;

pub use monte_carlo::MonteCarloSim;

pub use monte_carlo::MonteCarloResult;

pub use monte_carlo::Histogram;

pub use random_matrix::RandomMatrix;

pub use random_matrix::EigenvalueRenderer;

pub use sde::SDE;

pub use sde::SDERenderer;

pub use levy::LevyFlight;

pub use levy::CauchyFlight;

pub use levy::LevyRenderer;

pub use percolation::PercolationGrid;

pub use percolation::PercolationRenderer;

Modules

brownian

Brownian motion / Wiener process implementations.

geometric_bm

Geometric Brownian Motion (GBM) for modelling stock prices and multiplicative stochastic processes.

levy

Lévy flights: heavy-tailed random walks using alpha-stable distributions.

markov

Markov chains: discrete-time and continuous-time.

monte_carlo

Monte Carlo simulation framework.

ornstein_uhlenbeck

Ornstein-Uhlenbeck process: a mean-reverting stochastic process.

percolation

Percolation theory: site and bond percolation on 2D grids, cluster detection via union-find, spanning cluster identification, and critical threshold estimation.

poisson

Poisson processes: homogeneous, non-homogeneous, and compound.

prelude

Re-export common types for convenience.

random_matrix

Random matrix theory: GOE, GUE, Wishart matrices, eigenvalue computation, and spectral distribution analysis (Wigner semicircle, Marchenko-Pastur).

sde

Stochastic differential equations: generic SDE solver with Euler-Maruyama and Milstein methods, plus preset SDEs for common processes.