Spatio-temporal Ornstein-Uhlenbeck processes: theory, simulation and statistical inference
File(s)STOU_AcceptedCopy.pdf (2.91 MB)
Accepted version
Author(s)
Nguyen, M
Veraart, A
Type
Journal Article
Abstract
Spatio-temporal modelling is an increasingly popular topic in Statistics. Our paper contributes to this line of research
by developing the theory, simulation and inference for a spatio-temporal Ornstein-Uhlenbeck process. We conduct detailed
simulation studies and demonstrate the practical relevance of these processes in an empirical study of radiation
anomaly data. Finally, we describe how predictions can be carried out in the Gaussian setting.
by developing the theory, simulation and inference for a spatio-temporal Ornstein-Uhlenbeck process. We conduct detailed
simulation studies and demonstrate the practical relevance of these processes in an empirical study of radiation
anomaly data. Finally, we describe how predictions can be carried out in the Gaussian setting.
Date Issued
2016-09-15
Date Acceptance
2016-03-16
Citation
Scandinavian Journal of Statistics, 2016, 44 (1), pp.46-80
ISSN
1467-9469
Publisher
Wiley
Start Page
46
End Page
80
Journal / Book Title
Scandinavian Journal of Statistics
Volume
44
Issue
1
Copyright Statement
© 2016 Board of the Foundation of the Scandinavian Journal of Statistics
Sponsor
Commission of the European Communities
Imperial College London
Grant Number
FP7-PEOPLE-2012-CIG-321707
Subjects
Science & Technology
Physical Sciences
Statistics & Probability
Mathematics
moments-based inference
Ornstein-Uhlenbeck processes
spatio-temporal modelling
stochastic simulation
INFINITELY DIVISIBLE PROCESSES
MODELS
0104 Statistics
Publication Status
Published