Comparing implementations of global and local indicators of spatial association

Alam M, Rönnegård L, Shen X (2015) Fitting conditional and simultaneous autoregressive spatial models in hglm. R J 7(2):5–18. http://journal.r-project.org/archive/2015-2/alam-ronnegard-shen.pdf

Allaire JJ, Ushey K, Tang Y (2018) reticulate: interface to ’Python’. https://CRAN.R-project.org/package=reticulate , R package version 1.8

Anselin L (1992) SpaceStat, a software program for analysis of spatial data. National Center for Geographic Information and Analysis (NCGIA), University of California, Santa Barbara

Anselin L (1995) Local indicators of spatial association—LISA. Geogr Anal 27(2):93–115

Anselin L (1996) The Moran scatterplot as an ESDA tool to assess local instability in spatial association. In: Fischer MM, Scholten HJ, Unwin D (eds) Spatial analytical perspectives on GIS. Taylor & Francis, London, pp 111–125

Anselin L, Syabri I, Kho Y (2006) GeoDa: an introduction to spatial data analysis. Geogr Anal 38:5–22

Assunção R, Reis EA (1999) A new proposal to adjust Moran’s I for population density. Stat Med 18:2147–2162

Bivand RS (1992) SYSTAT-compatible software for modeling spatial dependence among observations. Comput Geosci 18(8):951–963. https://doi.org/10.1016/0098-3004(92)90013-H

Bivand RS (1998) Software and software design issues in the exploration of local dependence. The Statistician 47:499–508

Bivand RS (2006) Implementing spatial data analysis software tools in R. Geogr Anal 38:23–40

Bivand RS (2008) Implementing representations of space in economic geography. J Reg Sci 48:1–27

Bivand RS (2009) Applying measures of spatial autocorrelation: computation and simulation. Geogr Anal 41(375–384):10

Bivand RS, Gebhardt A (2000) Implementing functions for spatial statistical analysis using the R language. J Geogr Syst 2:307–317

Bivand RS, Piras G (2015) Comparing implementations of estimation methods for spatial econometrics. J Stat Softw 63(1):1–36. https://doi.org/10.18637/jss.v063.i18

Bivand RS, Portnov BA (2004) Exploring spatial data analysis techniques using R: the case of observations with no neighbours. In: Anselin L, Florax RJGM, Rey SJ (eds) Advances in spatial econometrics: methodology, tools, applications. Springer, Berlin, pp 121–142

Bivand RS, Müller W, Reder M (2009) Power calculations for global and local Moran’s I. Comput Stat Data Anal 53:2859–2872

Bivand RS, Sha Z, Osland L, Thorsen IS (2017) A comparison of estimation methods for multilevel models of spatially structured data. Spat Stat. https://doi.org/10.1016/j.spasta.2017.01.002

Bjornstad ON (2018) ncf: spatial covariance functions. https://CRAN.R-project.org/package=ncf , R package version 1.2-5

Caldas de Castro M, Singer BH (2006) Controlling the false discovery rate: a new application to account for multiple and dependent tests in local statistics of spatial association. Geogr Anal 38(2):180–208. https://doi.org/10.1111/j.0016-7363.2006.00682.x

Cliff AD, Ord JK (1969) The problem of spatial autocorrelation. In: Scott AJ (ed) London Papers in Regional Science 1, Studies in Regional Science. Pion, London, pp 25–55

Cliff AD, Ord JK (1971) Evaluating the percentage points of a spatial autocorrelation coefficient. Geogr Anal 3(1):51–62. https://doi.org/10.1111/j.1538-4632.1971.tb00347.x

Cliff AD, Ord JK (1973) Spatial autocorrelation. Pion, London

Cliff AD, Ord JK (1981) Spatial processes. Pion, London

Cressie NAC (1993) Statistics for spatial data. Wiley, New York

Duncan OD, Cuzzort RP, Duncan B (1961) Statistical geography: problems in analyzing areal data. Free Press, Glencoe

Geary RC (1954) The contiguity ratio and statistical mapping. Inc Stat 5:115–145

Getis A, Ord JK (1992) The analysis of spatial association by the use of distance statistics. Geogr Anal 24(2):189–206

Getis A, Ord JK (1993) Erratum: The analysis of spatial association by the use of distance statistics. Geogr Anal 25(3):276

Getis A, Ord JK (1996) Local spatial statistics: an overview. In: Longley P, Batty M (eds) Spatial analysis: modelling in a GIS environment. GeoInformation International, Cambridge, pp 261–277

Gómez-Rubio V, Ferrándiz-Ferragud J, López-Quílez A (2005) Detecting clusters of disease with R. J Geogr Syst 7(2):189–206

Goodchild MF (1986) Spatial autocorrelation. Geobooks, Norwich. https://alexsingleton.files.wordpress.com/2014/09/47-spatial-aurocorrelation.pdf

Hepple LW (1998) Exact testing for spatial autocorrelation among regression residuals. Environ Plan A 30:85–108

Kalogirou S (2017) lctools: local correlation, spatial inequalities, geographically weighted regression and other tools. https://CRAN.R-project.org/package=lctools , R package version 0.2-6

Levine N (2006) Crime mapping and the CrimeStat program. Geogr Anal 38(1):41–56

Levine N (2017) Crimestat: a spatial statistical program for the analysis of crime incidents. In: Shekhar S, Xiong H, Zhou X (eds) Encyclopedia of GIS. Springer, Cham, pp 381–388. https://doi.org/10.1007/978-3-319-17885-1_229

McMillen DP (2003) Spatial autocorrelation or model misspecification? Int Reg Sci Rev 26:208–217

Moran PAP (1950) Notes on continuous stochastic phenomena. Biometrika 37:17–23

Ord JK, Getis A (1995) Local spatial autocorrelation statistics: distributional issues and an application. Geogr Anal 27(3):286–306

Ord JK, Getis A (2001) Testing for local spatial autocorrelation in the presence of global autocorrelation. J Reg Sci 41(3):411–432

Ord JK, Getis A (2012) Local spatial heteroscedasticity (LOSH). Ann Reg Sci 48(2):529–539

Paradis E, Claude J, Strimmer K (2004) APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20:289–290

Rey SJ, Anselin L (2007) Pysal: a python library of spatial analytical methods. Rev Reg Stud 37(1):5–27

Rey SJ, Anselin L, Li X, Pahle R, Laura J, Li W, Koschinsky J (2015) Open geospatial analytics with pysal. ISPRS Int J Geoinf 4(2):815–836. https://doi.org/10.3390/ijgi4020815

Ripley BD (1981) Spatial statistics. Wiley, New York

Schabenberger O, Gotway CA (2005) Statistical methods for spatial data analysis. Chapman & Hall, Boca Raton

Scott LM, Janikas MV (2010) Spatial statistics in ArcGIS. In: Fischer MM, Getis A (eds) Handbook of applied spatial analysis: software tools, methods and applications. Springer, Berlin, pp 27–41. https://doi.org/10.1007/978-3-642-03647-7_2

Sokal RR, Oden NL (1978) Spatial autocorrelation in biology: 1. methodology. Biol J Linn Soc 10(2):199–228. https://doi.org/10.1111/j.1095-8312.1978.tb00013.x

Sokal RR, Oden NL, Thomson BA (1998) Local spatial autocorrelation in a biological model. Geogr Anal 30:331–354

Tiefelsdorf M (2000) Modelling spatial processes: the identification and analysis of spatial relationships in regression residuals by means of Moran’s I. Springer, Berlin

Tiefelsdorf M (2002) The saddlepoint approximation of Moran’s I and local Moran’s $${I}_i$$ I i reference distributions and their numerical evaluation. Geogr Anal 34:187–206

Tiefelsdorf M, Boots BN (1995) The exact distribution of Moran’s I. Environ Plan A 27:985–999

Tiefelsdorf M, Boots BN (1997) A note on the extremities of local Moran’s I and their impact on global Moran’s I. Geogr Anal 29:248–257

Westerholt R, Resch B, Zipf A (2015) A local scale-sensitive indicator of spatial autocorrelation for assessing high- and low-value clusters in multiscale datasets. Int J Geogr Inf Sci 29(5):868–887. https://doi.org/10.1080/13658816.2014.1002499

Westerholt R, Resch B, Mocnik FB, Hoffmeister D (2018) A statistical test on the local effects of spatially structured variance. Int J Geogr Inf Sci 32(3):571–600. https://doi.org/10.1080/13658816.2017.1402914

Wong DWS, Lee J (2005) Statistical analysis of geographic information with ArcView GIS and ArcGIS. Wiley, New York

Xu M, Mei CL, Yan N (2014) A note on the null distribution of the local spatial heteroscedasticity (LOSH) statistic. Ann Reg Sci 52(3):697–710