RT Journal Article
T1 The effect of the spatial domain in FANOVA models with ARH(1) error term
A1 Álvarez Liébana, Javier
A1 Ruiz Medina, María Dolores
A2 Chen, Ming-Hui
A2 Wang, Yuedong
AB Functional Analysis of Variance (FANOVA) from Hilbert-valued correlated data with spatial rectangular or circular supports is analyzed, when Dirichlet conditions are assumed on the boundary. Specifically, a Hilbert-valued fixed effect model with error term defined from an Autoregressive Hilbertian process of order one (ARH(1) process) is considered, extending the formulation given in [51]. A new statistical test is also derived to contrast the significance of the functional fixed effect parameters. The Dirichlet conditions established at the boundary affect the dependence range of the correlated error term. While the rate of convergence to zero of the eigenvalues of the covariance kernels, characterizing the Gaussian functional error components, directly affects the stability of the generalized least-squares parameter estimation problem. A simulation study and a real-data application related to fMRI analysis are undertaken to illustrate the performance of the parameter estimator and statistical test derived.
PB International Press of Boston
SN 1938-7989
YR 2017
FD 2017-05-30
LK https://hdl.handle.net/20.500.14352/95652
UL https://hdl.handle.net/20.500.14352/95652
LA eng
NO Álvarez Liébana, Javier, Ruiz-Medina, María. (2017). The effect of the spatial domain in FANOVA models with ARH(1) error term. Statistics and Its Interface. 10. 607-628.
DS Docta Complutense
RD 23 abr 2025