folie.BrownianMotion

class folie.BrownianMotion(mu=0, sigma=1.0, dim=1, **kwargs)

Model for (forced) Brownian Motion Parameters: \([\mu, \sigma]\)

\[dX(t) = \mu(X)dt + \sigma(X)dW_t\]

where:

\(\mu(X) = \mu\)

\(\sigma(X) = \sqrt{2\sigma}\)

Parameters:

mu: float or ndarray of shape (dim,)

sigma: float or ndarray of shape (dim,dim)

constant, >0

dim: int

Wanted dimension of the model

copy() → Model

Makes a deep copy of this model.

Returns:

copy

A new copy of this model.

exact_step(x, dt, dZ, t=0.0)

Simple Brownian motion can be simulated exactly

get_params(deep=False)

Get the parameters.

Returns:

paramsmapping of string to any

Parameter names mapped to their values.

set_params(**params)

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Parameters:

**paramsdict

Estimator parameters.

Returns:

selfobject

Estimator instance.

property coefficients

Access the coefficients

property coefficients_drift

Access the coefficients

property coefficients_drift_biased

Access the coefficients

property dim

Dimensionnality of the model

property has_exact_density: bool

Return true if model has an exact density implemented

Examples using folie.BrownianMotion

Likelihood functions

Likelihood functions