kalman

Functions

IntegratedKalmanFilter(kernel, X, y, t_states, obsid, ...)	Wrapper for integrated_kalman_filter function
integrated_kalman_filter(A_aug, Q_aug, H_aug, R, ...)	Jax implementation of the integrated Kalman filter algorithm

Module Contents

smolgp.solvers.integrated.kalman.IntegratedKalmanFilter(kernel, X, y, t_states, obsid, instid, stateid, R, return_v_S=False)

Wrapper for integrated_kalman_filter function

Parameters:

• kernel – IntegratedStateSpaceModel kernel

• X – Array of size N, data coordinates (e.g. (time, texp, instid))

• y – Array of size (N, D), measurements at the data coordinates

• t_states – Array of size K, sorted time coordinate of all states (exposure starts and ends)

• obsid – Array of size N, which observation (0,…,N-1) is being made at each state k

• instid – Array of size N, which instrument (0,…,Ninst-1) recorded observation n

• stateid – Array of size K, 0 for exposure-start, 1 for exposure-end

• R – Observation noise covariance, shape (N, D, D)

• return_v_S – Whether to return innovation and its covariance (for likelihood computation)

Returns:

filtered means P_filtered : filtered covariances m_predicted: predicted means P_predicted: predicted covariances

Return type:

m_filtered

smolgp.solvers.integrated.kalman.integrated_kalman_filter(A_aug, Q_aug, H_aug, R, RESET, X, y, t_states, obsid, instid, stateid, m0, P0)

Jax implementation of the integrated Kalman filter algorithm

See Section 3.2.1 in Rubenzahl & Hattori et al. (in prep) for detailed description of the algorithm and notation.