ode_em

Euler-Maruyama method implementation of the <acronym>ODE</acronym>.

A fast, scalable, and versatile framework for
simulating large systems with Gillespie's Stochastic Simulation
Algorithm ('SSA'). This package is the spiritual successor to the
'GillespieSSA' package originally written by Mario Pineda-Krch.
Benefits of this package include major speed improvements (>100x),
easier to understand documentation, and many unit tests that try to
ensure the package works as intended. Cannoodt and Saelens et al. (2021)
<doi:10.1038/s41467-021-24152-2>.

Robrecht Cannoodt

GillespieSSA2

Gillespie's Stochastic Simulation Algorithm for Impatient People

Wouter Saelens

ode_em function

<dl><dt>tau</dt>
<dd>tau parameter</dd>
<dt>noise_strength</dt>
<dd>noise_strength parameter</dd></dl>

Arguments

Euler-Maruyama method (EM) — ode_em

<dl>

<dt>tau</dt>
<dd>tau parameter</dd>


<dt>noise_strength</dt>
<dd>noise_strength parameter</dd>

</dl>

ode_em: Euler-Maruyama method (EM)

Description

Usage

Value

Arguments