Computationally efficient multilevel Gaussian process regression for functional data observed under completely or partially regular sampling designs

Adam Gorm Hoffmann; Claus Thorn Ekstrøm; Andreas Kryger Jensen

doi:10.1007/s11749-025-00996-4

Computationally efficient multilevel Gaussian process regression for functional data observed under completely or partially regular sampling designs

Adam Gorm Hoffmann^*, Claus Thorn Ekstrøm, Andreas Kryger Jensen

^*Corresponding author af dette arbejde

Biostatistisk afdeling

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

Originalsprog	Engelsk
Tidsskrift	Test
ISSN	1133-0686
DOI	https://doi.org/10.1007/s11749-025-00996-4
Status	E-pub ahead of print - 2025

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10.1007/s11749-025-00996-4

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Citationsformater

@article{bc9b683983cb472481bd8dcded0ec9c6,

title = "Computationally efficient multilevel Gaussian process regression for functional data observed under completely or partially regular sampling designs",

author = "Hoffmann, {Adam Gorm} and Ekstr{\o}m, {Claus Thorn} and Jensen, {Andreas Kryger}",

year = "2025",

doi = "10.1007/s11749-025-00996-4",

language = "English",

journal = "Test",

issn = "1133-0686",

publisher = "Springer",

}

TY - JOUR

T1 - Computationally efficient multilevel Gaussian process regression for functional data observed under completely or partially regular sampling designs

AU - Hoffmann, Adam Gorm

AU - Ekstrøm, Claus Thorn

AU - Jensen, Andreas Kryger

PY - 2025

Y1 - 2025

U2 - 10.1007/s11749-025-00996-4

DO - 10.1007/s11749-025-00996-4

M3 - Journal article

SN - 1133-0686

JO - Test

JF - Test

ER -