Comparative Spatial Filtering in Regression Analysis

By Arthur Getis, Daniel A. Griffith. 2002

353 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/601f229512d3710473f673718ac6430545b7e93a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Global and Planetary Change

Citations in the corpus

Spatial ordination of vegetation data using a generalization of Wartenberg's multivariate spatial correlation (2008, methodology): “Global indices such as Moran’s I and Geary’s c (Moran 1948; Geary 1954; Cliff & Ord 1973) and their local extensions (Anselin 1995) have been widely used to measure the spatial dependence and its local variations for one quantitative variable.”
Thirty years of spatial econometrics (2010, methodology): “Spatial filtering gains some attention as an approach to remove spatial correlation from variables in a range of models, including models for counts, e.g., in Getis and Griffith (2002); Griffith (2003); Griffith and Peres-Neto (2006); and Tiefelsdorf and Griffith (2007).”
County child poverty rates in the US: a spatial regression approach (2006, methodology): “Recent treatments include the work of Anselin (2000, 2001a, b, 2002), Anselin and Bera (1998), Getis and Griffith (2002), and Kelejian and Prucha (1997).”
Spatial modelling: a comprehensive framework for principal coordinate analysis of neighbour matrices (PCNM) (2006, methodology): “…called “space” for short in scientific papers) in multivariate analyses such as canonical correlation analysis (Gittins, 1985, Pélissier et al., 2002, Gimaret-Carpentier et al., 2003), canonical correspondence analysis (CCA, Borcard et al., 1992, Borcard and Legendre, 1994, Méot et al., 1998) or…”
Semiparametric Filtering of Spatial Autocorrelation: The Eigenvector Approach (2007, methodology): “A collaborative one-to-one comparison of both nonparametric spatial filtering approaches is given by their architects (Getis and Griffith, 2002).”
The Impact of Surrounding Land Use and Vegetation on Single-Family House Prices (2004, methodology): “…1990; Pace and Gilley, 1997), SAR with similarity components (Besner, 2002), spatial filtering techniques (Cliff and Ord, 1981; Getis, 1990; Getis and Griffith, 2002; Griffith, 1996), artificial neural networks (Din et al, 2001; Nguyen and Cripps, 2001; Tay and Ho, 1992; Worzala et al,…”
Spatial modeling in ecology: the flexibility of eigenfunction spatial analyses. (2006, background): “Getis and Griffith (2002) furnished a comparison between their individual formulations.”
The European Regional Convergence Process, 1980-1995: Do Spatial Regimes and Spatial Dependence Matter? (2006, background): “Some authors prefer to prewhiten or filter the variables to get rid of spatial autocorrelation (e.g., Getis and Griffith 2002, among others).”
A spatially filtered mixture of β-convergence regressions for EU regions, 1980–2002 (2008, background): “results in “cleaning up” the spatial effects from geographically organized variables ( Getis and Griffith 2002 ).”
Regional Convergence Clubs in Europe: Identification and Conditioning Factors (2012, methodology): “Therefore, before running the log t test, we apply Getis’ filter in order to eliminate the spatial component inherent in the data (Getis, 1995; Getis and Griffith, 2002).4 According to Getis’ filtering procedure, the spatially dependent variable is divided into a filtered nonspatial variable and a…”
Spatial Structure and Spatial Interaction: 25 Years Later (2007, neutral): “…types of spatial filters exist for georeferenced data analysis, namely spatial linear operators (e.g., Griffith 1979), Getis’s Gi specification (e.g., Getis and Griffith 2002), Griffith’s eigenfunction specification, and the Legendregroup’s PCNM specification (e.g., Griffith and Peres-Neto 2006).”