An analytical process of spatial autocorrelation functions based on Moran's index. [PDF]
PLoS ONE, 2021 A number of spatial statistic measurements such as Moran's I and Geary's C can be used for spatial autocorrelation analysis. Spatial autocorrelation modeling proceeded from the 1-dimension autocorrelation of time series analysis, with time lag replaced ...
Yanguang Chen
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Spatial Autocorrelation of COVID-19 in Slovakia [PDF]
Tropical Medicine and Infectious Disease, 2023 The pandemic situation of COVID-19, which affected almost the entire civilized world with its consequences, offered a unique opportunity for analysis of geographical space. In a relatively short period of time, the COVID-19 pandemic became a truly global
Katarína Vilinová +1 more
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When to use commuting zones? An empirical description of spatial autocorrelation in U.S. counties versus commuting zones [PDF]
PLoS ONE, 2022 U.S. Commuting Zones (CZs) are an aggregation of county-level data that researchers commonly use to create less arbitrary spatial entities and to reduce spatial autocorrelation.
Craig Wesley Carpenter +2 more
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Derivation of correlation dimension from spatial autocorrelation functions. [PDF]
PLoS ONEBackgroundSpatial complexity is always associated with spatial autocorrelation. Spatial autocorrelation coefficients including Moran's index proved to be an eigenvalue of the spatial correlation matrixes. An eigenvalue represents a kind of characteristic
Yanguang Chen
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Spatial autocorrelation equation based on Moran’s index [PDF]
Scientific Reports, 2023 Moran’s index is an important spatial statistical measure used to determine the presence or absence of spatial autocorrelation, thereby determining the selection orientation of spatial statistical methods.
Yanguang Chen
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The Spatial Autocorrelation Analysis For Transport Accessibility In Selected Regions Of The European Union [PDF]
Comparative Economic Research, 2016 In view of the significant differences between the socio-economic regions, the level of development of transport is not homogenous. According to Tobler’s law (1970) we can point out that all objects are related to each other, but the ones located closer ...
Joanna Górniak
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New framework of Getis-Ord's indexes associating spatial autocorrelation with interaction. [PDF]
PLoS ONE, 2020 Spatial autocorrelation and spatial interaction are two important analytical processes for geographical analyses. However, the internal relations between the two types of models have not been brought to light. This paper is devoted to integrating spatial
Yanguang Chen
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A wavelet-based method to remove spatial autocorrelation in the analysis of species distributional data [PDF]
Web Ecology, 2008 Species distributional data based on lattice data often display spatial autocorrelation. In such cases, the assumption of independently and identically distributed errors can be violated in standard regression models.
G. Carl, C. F. Dormann, I. Kühn
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Fast Spatial Autocorrelation [PDF]
2020 IEEE International Conference on Data Mining (ICDM), 2020 Physical or geographic location proves to be an important feature in many data science models, because many diverse natural and social phenomenon have a spatial component. Spatial autocorrelation measures the extent to which locally adjacent observations of the same phenomenon are correlated. Although statistics like Moran's $I$ and Geary's $C$ are
Anar Amgalan +2 more
openaire +3 more sources
Spatial autocorrelation and co-occurrence of six serovarieties of Leptospira in goat herds of the State of Guanajuato, Mexico. [PDF]
Braz J Microbiol, 2021 Gaytán-Camarillo F +5 more
europepmc +3 more sources