pymc.EulerMaruyama#

class pymc.EulerMaruyama(*args, **kwargs)[source]#

Stochastic differential equation discretized with the Euler-Maruyama method.

Parameters
dt: float

time step of discretization

sde_fn: callable

function returning the drift and diffusion coefficients of SDE

sde_pars: tuple

parameters of the SDE, passed as *args to sde_fn

Methods

EulerMaruyama.__init__(dt, sde_fn, sde_pars, ...)

EulerMaruyama.dist(*args, **kwargs)

Creates a tensor variable corresponding to the cls distribution.

EulerMaruyama.logp(x)

Calculate log-probability of EulerMaruyama distribution at specified value.

Attributes

rv_op

rv_type