Estimating sample paths of Gauss-Markov processes from noisy data

Benjamin Davies

Papers from arXiv.org

Abstract: I derive the pointwise conditional means and variances of an arbitrary Gauss-Markov process, given noisy observations of points on a sample path. These moments depend on the process's mean and covariance functions, and on the conditional moments of the sampled points. I study the Brownian motion and bridge as special cases.

Date: 2024-03
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