Journal article
Testing lack of symmetry in spatial–temporal processes
Journal of Statistical Planning and Inference, Vol.138(10), pp.2847-2866
10/2008
DOI: 10.1016/j.jspi.2007.10.021
PMCID: PMC2662627
PMID: 19337579
Abstract
Symmetry and separability of a covariance function are common assumptions to simplify the modeling effort of spatial–temporal processes. However, many studies in environmental sciences show that real data have complex spatial–temporal dependency structures resulting from lack of symmetry or violation of other standard assumptions of the covariance function. In this study, we propose new formal tests for lack of symmetry by using spectral representations of the spatial–temporal covariance functions of regularly spaced spatial–temporal data. The advantage of the proposed tests is that classical analysis of variance (ANOVA) models can be used for detecting lack of symmetry inherent in spatial–temporal processes. We evaluate the performance of the tests with simulation studies and we apply them to air pollution data.
Details
- Title: Subtitle
- Testing lack of symmetry in spatial–temporal processes
- Creators
- Man Sik Park - Department of Preventive Medicine, Medical Research Center for Environmental Toxico-Genomics and Proteomics, College of Medicine, Korea University, Seoul 136-705, Republic of KoreaMontserrat Fuentes - North Carolina State University
- Resource Type
- Journal article
- Publication Details
- Journal of Statistical Planning and Inference, Vol.138(10), pp.2847-2866
- DOI
- 10.1016/j.jspi.2007.10.021
- PMID
- 19337579
- PMCID
- PMC2662627
- NLM abbreviation
- J Stat Plan Inference
- ISSN
- 0378-3758
- eISSN
- 1873-1171
- Publisher
- Elsevier B.V
- Language
- English
- Date published
- 10/2008
- Academic Unit
- Statistics and Actuarial Science; Biostatistics; Provost Office Administration
- Record Identifier
- 9983765296402771
Metrics
25 Record Views