ELSA: a new local indicator for spatial association
There are several local indicators of spatial association (LISA) that allow exploration of local patterns in spatial data. Despite numerous situations where categorical variables are encountered, few attempts have been devoted to the development of methods to explore the local spatial pattern in cat...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/65130/ |
| Summary: | There are several local indicators of spatial association (LISA) that allow exploration of local patterns in spatial data. Despite numerous situations where categorical variables are encountered, few attempts have been devoted to the development of methods to explore the local spatial pattern in categorical data. To our knowledge, there is no indicator of local spatial association that can be used for both continuous and categorical data. We introduce ELSA, which can be used for exploring and testing local spatial association for continuous and categorical variables. We provide the R-package elsa for making these computations. |
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