Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - A class of convolution-based models for spatio-temporal processes with non-separable covariance structure
AU - Rodrigues, Alexandre
AU - Diggle, Peter J.
PY - 2010/12
Y1 - 2010/12
N2 - In this article, we propose a new parametric family of models for real-valued spatio-temporal stochastic processes S(x, t) and show how low-rank approximations can be used to overcome the computational problems that arise in fitting the proposed class of models to large datasets. Separable covariance models, in which the spatio-temporal covariance function of S(x, t) factorizes into a product of purely spatial and purely temporal functions, are often used as a convenient working assumption but are too inflexible to cover the range of covariance structures encountered in applications. We define positive and negative non-separability and show that in our proposed family we can capture positive, zero and negative non-separability by varying the value of a single parameter.
AB - In this article, we propose a new parametric family of models for real-valued spatio-temporal stochastic processes S(x, t) and show how low-rank approximations can be used to overcome the computational problems that arise in fitting the proposed class of models to large datasets. Separable covariance models, in which the spatio-temporal covariance function of S(x, t) factorizes into a product of purely spatial and purely temporal functions, are often used as a convenient working assumption but are too inflexible to cover the range of covariance structures encountered in applications. We define positive and negative non-separability and show that in our proposed family we can capture positive, zero and negative non-separability by varying the value of a single parameter.
KW - convolution-based models
KW - non-separability
KW - spatio-temporal processes
KW - TIME DATA
KW - SPACE
U2 - 10.1111/j.1467-9469.2009.00675.x
DO - 10.1111/j.1467-9469.2009.00675.x
M3 - Journal article
VL - 37
SP - 553
EP - 567
JO - Scandinavian Journal of Statistics
JF - Scandinavian Journal of Statistics
SN - 1467-9469
IS - 4
ER -