Library

LinearObservation(P, H, R)

Observe the LinearEvolution P using y = Hx + v where $v \sim N(0, R)$.

Examples

    O = LinearObservation(LinearEvolution(Φ, Gaussian(b, Q)), H, R)

LinearEvolution(Φ, b, Q) <: Evolution

Evolution of the law of x -> Φ x + w where $w \sim N(0, Q)$.

Examples

    evolve(LinearEvolution(Φ, b, Q), 0 => Gaussian(x, P))

LinearStateSpaceModel <: StateSpaceModel

LinearStateSpaceModel(sys, obs)

Combines a linear system sys and an observations model obs and to a linear statespace model in a modular way.

Evolves StateObs objects.

kalmanfilter(M, t => x0) -> kf

kf(iter) is an iterator over Gaussians or Distributions representing the filtered distribution of x where y iterates over (enumerated) signal values.

Example

kf = kalmanfilter(M, 0 => prior) #
est1 = collect(kf(Y1))
est2 = collect(kf(Y2))

filter(Y, P)

"Filter" data Y with iterator P calling (handling of nothings omitted)

(t, y), state = iterate(Y, state)
(s => x) = dyniterate(P, s => x, (observation = t => y,))