rts

Functions

ParallelRTSSmoother(kernel, X, kalman_results)	Wrapper for Parallel RTS smoother
make_associative_params(Phi, Q, t, mu, P)	Generate the associative parameters needed for parallel RTS
_combine_per_pair(left, right)
parallel_rts_smoother(asso_params)	Jax implementation of the parallel RTS smoother algorithm

Module Contents

smolgp.solvers.parallel.rts.ParallelRTSSmoother(kernel, X, kalman_results)

Wrapper for Parallel RTS smoother

Parameters:

• kernel – StateSpaceModel kernel

• X – input coordinates

• kalman_results – output from Kalman filter these are the filtered state means (b) and covariances (C)

Returns:

g: smoothed means L: smoothed covariances

Return type:

E

smolgp.solvers.parallel.rts.make_associative_params(Phi, Q, t, mu, P)

Generate the associative parameters needed for parallel RTS

See eqns in Section 4B of Sarkka & Garcia-Fernandez (2020)

smolgp.solvers.parallel.rts._combine_per_pair(left, right)

smolgp.solvers.parallel.rts.parallel_rts_smoother(asso_params)

Jax implementation of the parallel RTS smoother algorithm

See Section 4B of Sarkka & Garcia-Fernandez (2020) for a detailed description of the algorithm and notation.

Total runtime (span) complexity is ~O(logN) where N is the number of time steps.