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- W2791871566 abstract "Gravity type spatial interaction models have been popular among spatial scientists for many decades. Their more traditional specifications suffer from specification error attributable to, among other factors, spatial autocorrelation. This spatial autocorrelation has two components, a more conventional one relating to the geographic distributions of origin and destination phenomena, and a second one relating to the network of flows. Recent literature, to which this chapter contributes, reveals that spatial interaction model descriptions substantially improve with an accounting of network autocorrelation in Poisson regression estimation of parameters. Implementation of this specification requires eigenvector spatial filter construction, a principal topic of this chapter, which also furnishes parameter estimate comparisons for infill and increasing domain spatial sampling designs." @default.
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- W2791871566 date "2018-01-01" @default.
- W2791871566 modified "2023-09-23" @default.
- W2791871566 title "Spatial Autocorrelation and Spatial Interaction Gravity Models" @default.
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- W2791871566 doi "https://doi.org/10.1007/978-3-319-72553-6_9" @default.
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