Struct SDE

pub struct SDE { /* private fields */ }

Stochastic Differential Equation solver for pharmacometric models.

This struct represents a stochastic differential equation system and provides methods to simulate particles and estimate likelihood for PKPD modeling.

SDE models introduce stochasticity into the system dynamics, allowing for more realistic modeling of biological variability and uncertainty.

Implementations

impl SDE

pub fn new( drift: fn(_: &Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>, _: &Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>, _: f64, _: &mut Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>, _: Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>, _: &Covariates), diffusion: fn(_: &Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>, _: &mut Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>), lag: fn(_: &Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>) -> HashMap<usize, f64>, fa: fn(_: &Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>) -> HashMap<usize, f64>, init: fn(_: &Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>, _: f64, _: &Covariates, _: &mut Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>), out: fn(_: &Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>, _: &Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>, _: f64, _: &Covariates, _: &mut Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>), neqs: (usize, usize), nparticles: usize, ) -> SDE

Creates a new stochastic differential equation solver.

Arguments

• drift - Function defining the deterministic component of the SDE
• diffusion - Function defining the stochastic component of the SDE
• lag - Function to compute absorption lag times
• fa - Function to compute bioavailability fractions
• init - Function to initialize the system state
• out - Function to compute output equations
• neqs - Tuple containing the number of state and output equations
• nparticles - Number of particles to use in the simulation

Returns

A new SDE solver instance configured with the given components.

Trait Implementations

impl Clone for SDE

fn clone(&self) -> SDE

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for SDE

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

Formats the value using the given formatter.

impl Equation for SDE

fn estimate_likelihood( &self, subject: &Subject, support_point: &Vec<f64>, error_models: &ErrorModels, cache: bool, ) -> Result<f64, PharmsolError>

Estimates the likelihood of observed data given a model and parameters.

Arguments

• subject - Subject data containing observations
• support_point - Parameter vector for the model
• error_model - Error model to use for likelihood calculations
• cache - Whether to cache likelihood results for reuse

Returns

The log-likelihood of the observed data given the model and parameters.

fn kind() -> EqnKind

fn estimate_predictions( &self, subject: &Subject, support_point: &Vec<f64>, ) -> Result<Self::P, PharmsolError>

Generate predictions for a subject with given parameters.

fn nouteqs(&self) -> usize

Get the number of output equations in the model.

fn nstates(&self) -> usize

Get the number of state variables in the model.

fn simulate_subject( &self, subject: &Subject, support_point: &Vec<f64>, error_models: Option<&ErrorModels>, ) -> Result<(Self::P, Option<f64>), PharmsolError>

Simulate a subject with given parameters and optionally calculate likelihood.

impl EquationTypes for SDE

type S = Vec<Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>>

The state vector type

type P = ArrayBase<OwnedRepr<Prediction>, Dim<[usize; 2]>>

The predictions container type