 Testing Spatial Autocorrelation in Weighted Networks: The Modes Permutation TestFrançois Bavaud ()
Chapter Chapter 4 in Spatial Econometric Interaction Modelling, 2016, pp 67-83 from Springer Abstract: Abstract Permutation tests of spatial autocorrelation are justified under exchangeability, that is the premise that the observed scores follow a permutation-invariant joint distribution. Yet, in the frequently encountered case of geographical data collected on regions differing in importance, the variance of a regional score is expected to decrease with the size of the region, in the same way that the variance of an average is inversely proportional to the size of the sample in elementary statistics: heteroscedasticity holds in effect, already under spatial independence, thus weakening the rationale of the celebrated spatial autocorrelation permutation test (e.g. Cliff and Ord 1973; Besag and Diggle 1977) in the case of a weighted network. Keywords: Bootstrap; Local variance; Markov and semi-Markov processes; Moran’s I; Permutation test; Spatial autocorrelation; Spatial filtering; Weighted networks (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:adspcp:978-3-319-30196-9_4 Ordering information: This item can be ordered from DOI: 10.1007/978-3-319-30196-9_4 Access Statistics for this chapter More chapters in Advances in Spatial Science from Springer |
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