Functional Object Analysis: Toward Statistical Analysis of Functional Objects

Research output: Book/ReportPh.D. thesisResearch

Standard

Functional Object Analysis : Toward Statistical Analysis of Functional Objects . / Raket, Lars Lau.

Department of Computer Science, Faculty of Science, University of Copenhagen, 2014. 107 p.

Research output: Book/ReportPh.D. thesisResearch

Harvard

Raket, LL 2014, Functional Object Analysis: Toward Statistical Analysis of Functional Objects . Department of Computer Science, Faculty of Science, University of Copenhagen. <https://soeg.kb.dk/permalink/45KBDK_KGL/fbp0ps/alma99122493905005763>

APA

Raket, L. L. (2014). Functional Object Analysis: Toward Statistical Analysis of Functional Objects . Department of Computer Science, Faculty of Science, University of Copenhagen. https://soeg.kb.dk/permalink/45KBDK_KGL/fbp0ps/alma99122493905005763

Vancouver

Raket LL. Functional Object Analysis: Toward Statistical Analysis of Functional Objects . Department of Computer Science, Faculty of Science, University of Copenhagen, 2014. 107 p.

Author

Raket, Lars Lau. / Functional Object Analysis : Toward Statistical Analysis of Functional Objects . Department of Computer Science, Faculty of Science, University of Copenhagen, 2014. 107 p.

Bibtex

@phdthesis{4d1136f8ae344042b1124bea54ef34b2,
title = "Functional Object Analysis: Toward Statistical Analysis of Functional Objects ",
abstract = "We propose a direction it the field of statistics which we will call functional object analysis. This subfields considers the analysis of functional objects defined on continuous domains. In this setting we will focus on model-based statistics, with a particularly emphasis on mixed-effect formulations, where the observed functional signal is assumed to consist of both fixed and random functional effects. This thesis takes the initial steps toward the development of likelihood-based methodology for functional objects. We first consider analysis of functional data defined on high-dimensional Euclidean spaces under the effect of additive spatially correlated effects, and then move on to consider how to include data alignment in the statistical model as a nonlinear effect under additive correlated noise. In both cases, we will give directions on how to generalize the methodology to more complex data setups. Finally, we consider various extensions and future directions.",
author = "Raket, {Lars Lau}",
year = "2014",
language = "English",
publisher = "Department of Computer Science, Faculty of Science, University of Copenhagen",

}

RIS

TY - BOOK

T1 - Functional Object Analysis

T2 - Toward Statistical Analysis of Functional Objects

AU - Raket, Lars Lau

PY - 2014

Y1 - 2014

N2 - We propose a direction it the field of statistics which we will call functional object analysis. This subfields considers the analysis of functional objects defined on continuous domains. In this setting we will focus on model-based statistics, with a particularly emphasis on mixed-effect formulations, where the observed functional signal is assumed to consist of both fixed and random functional effects. This thesis takes the initial steps toward the development of likelihood-based methodology for functional objects. We first consider analysis of functional data defined on high-dimensional Euclidean spaces under the effect of additive spatially correlated effects, and then move on to consider how to include data alignment in the statistical model as a nonlinear effect under additive correlated noise. In both cases, we will give directions on how to generalize the methodology to more complex data setups. Finally, we consider various extensions and future directions.

AB - We propose a direction it the field of statistics which we will call functional object analysis. This subfields considers the analysis of functional objects defined on continuous domains. In this setting we will focus on model-based statistics, with a particularly emphasis on mixed-effect formulations, where the observed functional signal is assumed to consist of both fixed and random functional effects. This thesis takes the initial steps toward the development of likelihood-based methodology for functional objects. We first consider analysis of functional data defined on high-dimensional Euclidean spaces under the effect of additive spatially correlated effects, and then move on to consider how to include data alignment in the statistical model as a nonlinear effect under additive correlated noise. In both cases, we will give directions on how to generalize the methodology to more complex data setups. Finally, we consider various extensions and future directions.

UR - https://soeg.kb.dk/permalink/45KBDK_KGL/fbp0ps/alma99122493905005763

M3 - Ph.D. thesis

BT - Functional Object Analysis

PB - Department of Computer Science, Faculty of Science, University of Copenhagen

ER -

ID: 123353008