probnum.filtsmooth

Bayesian filtering and smoothing.

Functions

generate_cd(dynmod, measmod, initrv, times)	Samples true states and observations at pre-determined timesteps “times” for a continuous-discrete model.
generate_dd(dynmod, measmod, initrv, times)	Samples true states and observations at pre-determined timesteps “times” for a continuous-discrete model.

Classes

GaussFiltSmooth(dynamod, measmod, initrv)	Interface for Gaussian filtering and smoothing.
Kalman(dynamod, measmod, initrv)	Kalman filtering and smoothing for continuous-discrete and discrete-discrete state space models.
ExtendedKalman(dynamod, measmod, initrv)	Factory method for Kalman filters.
UnscentedKalman(dynamod, measmod, initrv)	Factory method for Unscented Kalman filters.
UnscentedTransform(dimension[, spread, …])	Used for unscented Kalman filter.
Transition	Markov transition rules in discrete or continuous time.
ContinuousModel	Markov transition rules in continuous time.
LinearSDEModel(driftmatrixfct, forcfct, …)	Linear, continuous-time Markov models given by the solution of the linear stochastic differential equation (SDE),
LTISDEModel(driftmatrix, force, dispmatrix, …)	Linear time-invariant continuous Markov models of the form dx = [F x(t) + u] dt + L dBt.
DiscreteModel	Transition models for discretely indexed processes.
DiscreteGaussianModel(dynafct, diffmatfct[, …])	Discrete Gaussian transition models of the form
DiscreteGaussianLinearModel(dynamatfct, …)	Discrete, linear Gaussian transition models of the form
DiscreteGaussianLTIModel(dynamat, forcevec, …)	Discrete, linear, time-invariant Gaussian transition models of the form
FiltSmoothPosterior	Posterior Distribution over States after Filtering/Smoothing
KalmanPosterior(locations, state_rvs, …)	Posterior Distribution after (Extended/Unscented) Kalman Filtering/Smoothing

Class Inheritance Diagram