folie.OrnsteinUhlenbeck¶
- class folie.OrnsteinUhlenbeck(theta=0, kappa=1.0, sigma=1.0, dim=1, **kwargs)[source]¶
Model for OU (ornstein-uhlenbeck): Parameters: \([\kappa, \mu, \sigma]\)
\[dX(t) = \mu(X,t)*dt + \sigma(X,t)*dW_t\]- where:
\(\mu(X,t) = \theta - \kappa X\)
\(\sigma(X,t) = \sqrt{2 \sigma}\)
- Parameters:
- theta, kappa: float or ndarray of shape (dim,)
- sigma: float or ndarray of shape (dim,dim)
constant, >0
- dim: int
Wanted dimension of the model
- get_params(deep=False)[source]¶
Get the parameters.
- Returns:
- paramsmapping of string to any
Parameter names mapped to their values.
- set_params(**params)[source]¶
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
