A - Papers appearing in refereed journals
Harris, P., Brunsdon, C., Lu, B., Nakaya, T. and Charlton, M. 2017. Introducing bootstrap methods to investigate coefficient non-stationarity in spatial regression models. Spatial Statistics. 21, pp. 241-261. https://doi.org/10.1016/j.spasta.2017.07.006
Authors | Harris, P., Brunsdon, C., Lu, B., Nakaya, T. and Charlton, M. |
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Abstract | In this simulation study, parametric bootstrap methods are introduced to test for spatial non-stationarity in the coefficients of regression models. Such a test can be rather simply conducted by comparing a model such as geographically weighted regression (GWR) as an alternative to a standard linear regression, the null hypothesis. In this study however, three spatially autocorrelated regressions are also used as null hypotheses: (i) a simultaneous autoregressive error model; (ii) a moving average error model; and (iii) a simultaneous autoregressive lag model. This expansion of null hypotheses, allows an investigation as to whether the spatial variation in the coefficients obtained using GWR could be attributed to some other spatial process, rather than one depicting non-stationary relationships. The new test is objectively assessed via a simulation experiment that generates data and coefficients with known multivariate spatial properties, all within the spatial setting of the oft-studied Georgia educational attainment data set. By applying the bootstrap test and associated contextual diagnosticsto pre-specified, area-based, geographical processes, our study |
Keywords | Geographically weighted regression; Spatial regression; Hypothesis testing; Collinearity; GWmodel |
Year of Publication | 2017 |
Journal | Spatial Statistics |
Journal citation | 21, pp. 241-261 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.spasta.2017.07.006 |
Open access | Published as non-open access |
Funder | Biotechnology and Biological Sciences Research Council |
National Natural Science Foundation of China | |
Funder project or code | The North Wyke Farm Platform [2012-2017] |
Output status | Published |
Publication dates | |
29 Jul 2017 | |
Publication process dates | |
Accepted | 24 Jul 2017 |
Copyright license | CC BY |
Publisher | Elsevier Sci Ltd |
ISSN | 2211-6753 |
Permalink - https://repository.rothamsted.ac.uk/item/84711/introducing-bootstrap-methods-to-investigate-coefficient-non-stationarity-in-spatial-regression-models
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