canari.component.white_noise_component

class canari.component.white_noise_component.WhiteNoise(std_error: float | None = 0.05)

Bases: BaseComponent

WhiteNoise class, inheriting from Canari’s BaseComponent. It is used to model zero-mean i.i.d. Gaussian errors.

Parameters:

std_error (Optional[float]) – Standard deviation of the error. Default is 0.05.

Examples

>>> from canari.component import WhiteNoise
>>> white_noise = WhiteNoise(std_error=0.5)
>>> white_noise.transition_matrix
array([[0]])
>>> white_noise.process_noise_matrix
array([[0.25]])

initialize_component_name()

Initialize the component’s name. str.

initialize_mu_states()

Initialize the mean of the hidden states. Output an 2D array.

initialize_num_states()

Initialize the number of hidden states. int.

initialize_observation_matrix()

Initialize the observation matrix. Output an 2D array.

initialize_process_noise_matrix()

Initialize the process noise covariance matrix. Output an 2D array.

initialize_states_name()

Initialize the names of all hidden states. list[str].

initialize_transition_matrix()

Initialize the transition matrix. Output an 2D array.

initialize_var_states()

Initialize the covariance matrix of the hidden states. Output an 2D array.