Priestorová analýza kriminality: jednorozmerný a viacrozmerný prístup
Klíčová slova:
kriminalita, priestorová analýza, lokálna jednorozmerná a viacrozmerná Gearyho štatistikaAbstrakt
Príspevok sa zaoberá priestorovou analýzou kriminality v NUTS 3 (Nomenclature of Units for Territorial Statistics) regiónoch krajín Vyšehradskej štvorky. Využíva vybrané nástroje exploratačnej analýzy priestorových dát ESDA, ktoré umožňujú skúmať štruktúru analyzovaných údajov, zisťovať prítomnosť priestorovej závislosti a existenciu priestorových zhlukov. Lokálna priestorová závislosť bola preskúmaná pomocou jednorozmernej Gearyho štatistiky a pri uvažovaní ďalších relevantných premenných (HDP na obyvateľa, miera zamestnanosti a hustota obyvateľstva) tiež pomocou viacrozmernej Gearyho štatistiky. Kým lokálna jednorozmerná Gearyho štatistika umožňuje identifikovať podobnosť alebo rozdielnosť hodnôt v susedných regiónoch pri uvažovaní jednej premennej, jej viacrozmerná verzia umožňuje porovnať geograficky susedné regióny z viacrozmerného hľadiska.Reference
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2. Anselin, L., Cohen, J., Cook, D., Gorr, W., & Tita, G. (2000). Spatial Analyses of Crime. In Criminal justice 2000: Vol. 4. Measurement and analysis of crime and justice. (pp. 213-262). Washington, DC: National Institute of Justice.
3. Anselin, L. (2019a). A Local Indicator of Multivariate Spatial Association: Extending Geary’s c. Geographical Analysis, 51(2), 133-150. doi: 10.1111/gean.12164
4. Anselin, L. (2019b). GeoDa An Introduction to Spatial Data Analysis, Local Spatial Autocorrelation (1). Univariate Local Statistics. Retrieved May 24, 2020, from https://geodacenter.github.io/workbook/6a_local_auto/lab6a.html#local-geary.
5. Anselin, L. (2019c). GeoDa An Introduction to Spatial Data Analysis. Local Spatial Autocorrelation (2). Advanced Topics. Retrieved May 24, 2020, from https://geodacenter.github.io/workbook/6b_local_adv/lab6b.html#multivariate-local-geary.
6. Dray, S., & Jombart, T. (2011). Revisiting Guerry’s data: Introducing spatial constraints in multivariate analysis. The Annals of Applied Statistics, 5(4), 2278-2299. doi: 10.1214/10-AOAS356
7. Eurostat. (2018a). Retrieved June 24, 2018, from http://ec.europa.eu/eurostat/web/rural-development/data/database.
8. Eurostat. (2018b). Retrieved June 24, 2018, from http://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units.
9. Fischer, M.M., & Wang, J. (2011). Spatial Data Analysis. Models, Methods and Techniques. Heidelberg: Springer.
10. Friendly, M. (2007). A.-M. Guerry’s Moral Statistics of France: Challenges for multivariable spatial analysis. Statistical Science, 22(3), 368-399. doi: 10.1214/07-STS241.
11. Furková, A. (2019). Spatial Cluster Analysis of the Regional Poverty in the European Union. In Proceedings of the International Conference on Contemporary Issues in Economics, Management and Business. Hanoi: National Economics University Publishing House, 873-883.
12. Geary, R. (1954). The contiguity ratio and statistical mapping. The Incorporated Statistician, 5, 115-145. doi: 10.2307/2986645.
13. Hungarian Central Statistical Office. (2018). Number of registered crimes by selected groups of crimes (2000–). Retrieved June 27, 2018, from https://www.ksh.hu/docs/eng/xstadat/xstadat_annual/i_zji001b.html.
14. Chocholatá, M. (2018a). Spatial econometric analysis of crime: Evidence from NUTS 3 regions of V4 countries. In Proceedings of the 34th International Scientific Conference on Economic and Social Development – XVIII International Social Congress (ISC-2018). Moscow, Varazdin: Varazdin Development and Entrepreneurship Agency, 194-202.
15. Chocholatá, M. (2018b). Crime Determinants from the Spatial Perspective: a GWR Approach. In Nové trendy v ekonometrii a operačním výzkumu, zborník príspevkov z mezinárodního vědeckého semináře, Praha, Bratislava: Vydavateľstvo EKONÓM, 68-76.
16. Messner, S.F., Anselin L., Baller, R.D., Hawkins, D.F., Deane, G., & Tolnay, S.E. (1999). The spatial patterning of county homicide rates: an application of exploratory spatial data analysis. Journal of Quantitative Criminology, 15(4), 423-450. doi: 10.1023/A:1007544208712.
17. Policie České republiky. (2018). Statistické přehledy kriminality za rok 2016. Retrieved June 27, 2018, from http://www.policie.cz/docDetail.aspx?docid=22346473&docType=ART.
18. Ratcliffe, J. (2010). Crime Mapping: Spatial and Temporal Challenges. In: Handbook of Quantitative Criminology (pp. 5-24), New York: Springer-Verlag.
19. Statistics Poland. (2018). Statistical Yearbook of the Regions - Poland 2017. Retrieved June 27, 2018, from https://stat.gov.pl/en/topics/statistical-yearbooks/statistical-yearbooks/statistical-yearbook-of-the-regions-poland-2017,4,12.html.
20. Štatistický úrad Slovenskej republiky. (2018). DATAcube. Database. Retrieved June 27, 2018, from http://datacube.statistics.sk/#!/view/sk/VBD_SK_WIN/sk3003rr/Kriminalita%20pod%C4%BEa%20z%C3%A1kladn%C3%BDch%20skup%C3%ADn%20trestn%C3%BDch%20%C4%8Dinov%20%5Bsk3003rr%5D
