A nonlinear mixed-effects model for simultaneous smoothing and registration of functional data

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

A nonlinear mixed-effects model for simultaneous smoothing and registration of functional data. / Raket, Lars Lau; Sommer, Stefan Horst; Markussen, Bo.

In: Pattern Recognition Letters, Vol. 38, 2014, p. 1-7.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Raket, LL, Sommer, SH & Markussen, B 2014, 'A nonlinear mixed-effects model for simultaneous smoothing and registration of functional data', Pattern Recognition Letters, vol. 38, pp. 1-7. https://doi.org/10.1016/j.patrec.2013.10.018

APA

Raket, L. L., Sommer, S. H., & Markussen, B. (2014). A nonlinear mixed-effects model for simultaneous smoothing and registration of functional data. Pattern Recognition Letters, 38, 1-7. https://doi.org/10.1016/j.patrec.2013.10.018

Vancouver

Raket LL, Sommer SH, Markussen B. A nonlinear mixed-effects model for simultaneous smoothing and registration of functional data. Pattern Recognition Letters. 2014;38:1-7. https://doi.org/10.1016/j.patrec.2013.10.018

Author

Raket, Lars Lau ; Sommer, Stefan Horst ; Markussen, Bo. / A nonlinear mixed-effects model for simultaneous smoothing and registration of functional data. In: Pattern Recognition Letters. 2014 ; Vol. 38. pp. 1-7.

Bibtex

@article{e1e9cad9a1aa4b598013b5dbebe9cec3,
title = "A nonlinear mixed-effects model for simultaneous smoothing and registration of functional data",
abstract = "We consider misaligned functional data, where data registration is necessary for proper statistical analysis. This paper proposes to treat misalignment as a nonlinear random effect, which makes simultaneous likelihood inference for horizontal and vertical effects possible. By simultaneously fitting the model and registering data, the proposed method estimates parameters and predicts random effects more precisely than conventional methods that register data in preprocessing. The ability of the model to estimate both hyperparameters and predict horizontal and vertical effects are illustrated on both simulated and real data.",
author = "Raket, {Lars Lau} and Sommer, {Stefan Horst} and Bo Markussen",
year = "2014",
doi = "10.1016/j.patrec.2013.10.018",
language = "English",
volume = "38",
pages = "1--7",
journal = "Pattern Recognition Letters",
issn = "0167-8655",
publisher = "Elsevier BV * North-Holland",

}

RIS

TY - JOUR

T1 - A nonlinear mixed-effects model for simultaneous smoothing and registration of functional data

AU - Raket, Lars Lau

AU - Sommer, Stefan Horst

AU - Markussen, Bo

PY - 2014

Y1 - 2014

N2 - We consider misaligned functional data, where data registration is necessary for proper statistical analysis. This paper proposes to treat misalignment as a nonlinear random effect, which makes simultaneous likelihood inference for horizontal and vertical effects possible. By simultaneously fitting the model and registering data, the proposed method estimates parameters and predicts random effects more precisely than conventional methods that register data in preprocessing. The ability of the model to estimate both hyperparameters and predict horizontal and vertical effects are illustrated on both simulated and real data.

AB - We consider misaligned functional data, where data registration is necessary for proper statistical analysis. This paper proposes to treat misalignment as a nonlinear random effect, which makes simultaneous likelihood inference for horizontal and vertical effects possible. By simultaneously fitting the model and registering data, the proposed method estimates parameters and predicts random effects more precisely than conventional methods that register data in preprocessing. The ability of the model to estimate both hyperparameters and predict horizontal and vertical effects are illustrated on both simulated and real data.

U2 - 10.1016/j.patrec.2013.10.018

DO - 10.1016/j.patrec.2013.10.018

M3 - Journal article

VL - 38

SP - 1

EP - 7

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

SN - 0167-8655

ER -

ID: 74858912