Struct MultiLevelMonteCarlo 

pub struct MultiLevelMonteCarlo { /* private fields */ }

Multi-level Monte Carlo estimator for variance reduction

MLMC uses a telescoping sum across multiple levels of approximation to achieve better convergence rates than standard Monte Carlo methods. This is particularly useful for stochastic differential equations and option pricing.

Implementations

impl MultiLevelMonteCarlo

pub fn new(max_levels: usize, base_samples: usize) -> Self

Create a new MLMC estimator

pub fn with_tolerance(self, tolerance: f64) -> Self

Set variance tolerance for adaptive level selection

pub fn with_convergence_factor(self, factor: f64) -> Self

Set convergence factor for sample size scaling

pub fn estimate<F>(&self, level_function: F) -> Result<MLMCResult, String>

where F: FnMut(usize, usize) -> Result<Vec<f64>, String>,

Estimate using multi-level Monte Carlo

pub fn estimate_parallel<F>( &self, level_function: F, ) -> Result<MLMCResult, String>

where F: Fn(usize, usize) -> Result<Vec<f64>, String> + Send + Sync,

Parallel MLMC estimation using thread pool

Trait Implementations

impl Clone for MultiLevelMonteCarlo

fn clone(&self) -> MultiLevelMonteCarlo

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for MultiLevelMonteCarlo

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.