Communications in Mathematical Sciences · 2005 · 80 citations · 12 references
EngineeringMathematicsProbability TheoryStochastic ModelingStochastic ProcessesGaussian Process ModelingGaussian ProcessesKalman FilteringState-space ModelsStochastic CalculusStochastic Differential EquationsFiltering TheoryGaussian Random ProcessesPath Sampling
In many applications it is important to be able to sample paths of SDEs conditional on observations of various kinds. This paper studies SPDEs which solve such sampling problems. The SPDE may be viewed as an infinite dimensional analogue of the Langevin SDE used in finite dimensional sampling. Here the theory is developed for conditioned Gaussian processes for which the resulting SPDE is linear. Applications include the Kalman-Bucy filter/smoother. A companion paper studies the nonlinear case, building on the linear analysis provided here.
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