Gaussian Process Regression for Scalar and Functional Inputs with funGp - The in-depth tour - Archive ouverte HAL
Pré-Publication, Document De Travail Année : 2020

Gaussian Process Regression for Scalar and Functional Inputs with funGp - The in-depth tour

Résumé

This is a comprehensive guide to creating and manipulating Gaussian process regression models using the R package funGp. It illustrates through examples, the usage of every function in the package and each example is accompanied by a code snippet to shorten the learning curve through direct usage of the functions.
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Dates et versions

hal-02536624 , version 1 (08-04-2020)
hal-02536624 , version 2 (28-10-2022)

Identifiants

  • HAL Id : hal-02536624 , version 1

Citer

José Daniel Betancourt, François Bachoc, Thierry Klein. Gaussian Process Regression for Scalar and Functional Inputs with funGp - The in-depth tour. 2020. ⟨hal-02536624v1⟩

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