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Communication Dans Un Congrès Année : 2015

Tuning interpolation methods for environmental uni-dimensional (transect) surveys

Résumé

The paper proposes rCV, a new randomized Cross Validation (CV) criterion specially designed for use with data acquired over non-uniformly scattered designs, like the linear transect surveys typical in environmental observation. The new criterion enables a robust parameterisation of interpolation algorithms, in a manner completely driven by the data and free of any modelling assumptions. The new CV method randomly chooses the hold-out sets such that they reflect, statistically, the geometry of the design with respect to the unobserved points of the area where the observations are to be extrapolated, minimizing biases due to the particular geometry of the designs. Numerical results on both simulated and realistic datasets show its robustness and superiority, leading to interpolated fields with smaller error.
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Dates et versions

hal-01318124 , version 1 (19-05-2016)

Identifiants

  • HAL Id : hal-01318124 , version 1

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You Li, Maria-João Rendas. Tuning interpolation methods for environmental uni-dimensional (transect) surveys. OCEANS 2015, IEES OES, Oct 2015, Washington DC, United States. ⟨hal-01318124⟩
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