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