pymc.EulerMaruyama

class pymc.EulerMaruyama(name, dt, sde_fn, *args, steps=None, **kwargs)

Stochastic differential equation discretized with the Euler-Maruyama method.

Parameters

dtfloat

time step of discretization

sde_fncallable()

function returning the drift and diffusion coefficients of SDE

sde_parstuple

parameters of the SDE, passed as *args to sde_fn

init_distunnamed distribution, optional

Scalar distribution for initial values. Unnamed refers to distributions created with the .dist() API. Distributions should have shape (*shape[:-1]). If not, it will be automatically resized. Defaults to pm.Normal.dist(0, 100, shape=…).

Warning

init_dist will be cloned, rendering it independent of the one passed as input.

Methods

EulerMaruyama.__init__(*args, **kwargs)
EulerMaruyama.dist(dt, sde_fn, sde_pars, *)	Creates a tensor variable corresponding to the cls distribution.
EulerMaruyama.rv_op(init_dist, steps, ...[, ...])