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Functional Calculus for Computational Statistics

Objective

Computations with spatial or spatiotemporal data occur in various areas such as the social and environmental sciences. The technological progress in data collection and storage capacities in recent years has caused a tremendous growth in data, and thereby exposed the limitations of state-of-the-art computational methods for statistical inference and predictions. Achieving computational feasibility severely limits the dependency structures of underlying random processes in currently deployed models. Above all, there is a strong need for methodologies that capture intricate spatial or spatiotemporal dependencies.
This project seeks to characterize flexible dependency structures by means of functional calculus and to exploit this characterization for efficient computations with Gaussian processes. My overall aim consists of a systematic construction and approximation of covariance operators, corresponding to sophisticated nonlocal dependencies, via the action of functions on local linear differential operators.
To establish numerical methods for operator functions, I will consider contour integral representations. Expedient transformations of the contours will facilitate operator-valued quadratures based on sinc approximations, which I will combine with uniformly stable discretizations for variational formulations of partial differential equations (PDEs) such as elliptic diffusion, parabolic and Stokes equations. To derive sharp rates of convergence, I will employ discrete inf-sup theory. Thereby I will address specific classes of functions and of differential operators suitable for inference from data. A particular focus will be on spatiotemporal statistical models based on fractional powers of non-autonomous parabolic operators, for which I will analyse space-time finite element methods.
This project will considerably strengthen the interaction between Numerical Analysis and Statistics by enabling PDE-based methodologies for efficient computations with spatial data.

Fields of science (EuroSciVoc)

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This project's classification has been human-validated.

Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2025-STG

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Host institution

TECHNISCHE UNIVERSITEIT DELFT
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 497 370,00
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 497 370,00

Beneficiaries (1)

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