We consider the problem of positive-semidefinite continuation: extending a partially specified covariance kernel from a subdomain Ω of [0,1]^2 to a covariance kernel on the entire domain [0,1]^2. We demonstrate that for broad domain classes, a canonical completion always exists and can be explicitly constructed. We characterise all possible completions as suitable perturbations of the canonical completion, and determine necessary and sufficient conditions for a unique completion to exist. We interpret the canonical completion via the graphical model structure it induces on the associated Gaussian process. Furthermore, we show how the estimation of the canonical completion reduces to the solution of a system of linear statistical inverse problems in the space of Hilbert-Schmidt operators, and derive rates of convergence under standard source conditions. We conclude by providing extensions of our theory to more general forms of domains, and by demonstrating how our results can be used to construct covariance estimators from sample path fragments of the associated stochastic process.
Based on joint work with K.G. Waghmare, EPFL
Link to the working paper: https://arxiv.org/abs/2107.07350
Personal Website of Victor M. Panaretos
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