Spatio-temporal autocorrelation of road network data
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Black WR (1992) Network autocorrelation in transportation network and flow systems. Geogr Anal 24(3):207–222
Black WR, Thomas I (1998) Accidents on Belgium’s motorways: a network autocorrelation analysis. J Transp Geogr 6(1):23–31
Box G, Jenkins G (1970) Time series analysis: forecasting and control. Holden-Day, San Francisco
Castells M (2010) Globalisation, networking, urbanisation: reflections on the spatial dynamics of the Information Age. Urban Stud 47(13):2737–2745
Chandra S, Al-Deek H (2008) Cross-correlation analysis and multivariate prediction of spatial time series of freeway traffic speeds. Transp Res Rec 2061:64–76
Chun Y (2008) Modeling network autocorrelation within migration flows by eigenvector spatial filtering. J Geogr Syst 10(4):317–344
Cliff AD, Ord JK (1969) The problem of spatial autocorrelation. In: Scott AJ (ed) Lond Pap in Reg Sci. Pion, London, pp 25–55
De Montis A, Caschili S, Chessa A (2011) Time evolution of complex networks: commuting systems in insular Italy. J. Geogr Syst 13(1):49–65
Ding Q, Wang X, Zhang X, Sun Z (2011) Forecasting traffic volume with space-time ARIMA model. Adv Mater Res 156–157:979–983
Doreian P, Teuter K, Wang C (1984) Network autocorrelation models: some Monte Carlo results. Sociol Methods Res 13(2):155–200
Dougherty MS, Cobbett MR (1997) Short-term inter-urban traffic forecasts using neural networks. Int J Forecast 13(1):21–31
Dow MM (2007) Galton’s problem as multiple network autocorrelation effects: cultural trait transmission and ecological constraint. Cross-Cult Res 41(4):336–363
Dow MM, Eff EA (2008) Global, regional, and local network autocorrelation in the standard cross-cultural sample. Cross-Cult Res 42(2):148–171
Dow MM, Burton ML, White DR, Reitz KP (1984) Galton’s problem as network autocorrelation. Am Ethnolog 11(4):754–770
Elhorst JP (2003) Specification and estimation of spatial panel data models. Int Reg Sci Rev 26(3):244–268
Farber S, Páez A, Volz E (2009) Topology and dependency tests in spatial and network autoregressive models. Geogr Anal 41(2):158–180
Flahaut B, Mouchart M, San Martin E, Thomas I (2003) The local spatial autocorrelation and the kernel method for identifying black zones: a comparative approach. Accid Anal Prev 35(6):991–1004
Florax RJGM, Rey S (1995) The impact of misspecified spatial structure in linear regression models. In: Anselin L, Florax RJGM (eds) New Dir in Spat Econom. Springer-Verlag, Berlin, pp 111–135
Geary RC (1954) The contiguity ratio and statistical mapping. Inc Stat 5(3):115–145
Getis A, Aldstadt J (2004) Constructing the spatial weights matrix using a local statistic. Geogr Anal 36(2):90–104
Griffith DA (1996) Some guidelines for specifying the geographic weights matrix contained in spatial statistical models. In: Arlinghaus SL, Griffith DA, Drake WD, Nystuen JD (eds) Pract Handb of Spat Stat. CRC Press, Boca Raton, FL, pp 82–148
Griffith DA (2010) Modeling spatio-temporal relationships: retrospect and prospect. J Geogr Syst 12(2):111–123
Griffith DA, Heuvelink GB (2009) Deriving space–time variograms from space–time autoregressive (STAR) model specifications. In StatGIS 2009 conference, Milos, Greece, June
Griffith DA, Lagona F (1998) On the quality of likelihood-based estimators in spatial autoregressive models when the data dependence structure is misspecified. J Stat Plan Inference 69(1):153–174
Hackney JK, Bernard M, Bindra S, Axhausen KW (2007) Predicting road system speeds using spatial structure variables and network characteristics. J. Geogr Sys 9(4):397–417
Hardisty F, Klippel A (2010) Analysing spatio-temporal autocorrelation with LISTA-Viz. Int J Geogr Inf Sci 24(10):1515–1526
Jiang B (2007) A topological pattern of urban street networks: universality and peculiarity. Physica A 384(2):647–655
Leenders RT (2002) The specification of weight structures in network autocorrelation models of social influence. SOM rep ser No. 02B09
Liu H, van Zuylen HJ, van Lint H, Salomons M (2006) Predicting urban arterial travel time with state-space neural networks and kalman filters. Transp Res Rec J Transp Res Board 1968(1):99–108
Min W, Wynter L, Amemiya Y (2007) Road traffic prediction with spatio-temporal correlations. In: Proceedings of the sixth trienn symp on transp anal, phuket Island, Thailand, June 2007
Min X, Hu J, Chen Q, Zhang T, Zhang Y (2009) Short-term traffic flow forecasting of urban network based on dynamic STARIMA model. In: Proceedings of the 12th international IEEE conference on intelligent transportation systems, St. Louis, Missouri, USA, 3–7 Oct 2009
Min X, Hu J, Zhang Z (2010) Urban traffic network modeling and short-term traffic flow forecasting based on GSTARIMA model. In: Proceedings of the 13th international IEEE conference on intelligent transportation systems, 19–22 Sept 2010, pp 1535–1540
Mizruchi MS, Neuman EJ (2008) The effect of density on the level of bias in the network autocorrelation model. Soc Netw 30:190–200
Neuman EJ, Mizruchi MS (2010) Structure and bias in the network autocorrelation model. Soc Netw 32(4):290–300
Olden JD, Neff BD (2001) Cross-correlation bias in lag analysis of aquatic time series. Marine Biol 138(5):1063–1070
Páez A, Scott DM, Volz E (2008) Weight matrices for social influence analysis: an investigation of measurement errors and their effect on model identification and estimation quality. Soc Netw 30(4):309–317
Patil GP (2009) Impacts and Wider Impacts on Statistics (of Cliff and Ord’s 1969 article on Spatial Autocorrelation). Geogr Anal 41(4):430–435
Pfeifer PE, Deutsch SJ (1980) A three-stage iterative procedure for space-time modelling. Technometrics 22(1):35–47
Pflieger G, Rozenblat C (2010) Introduction. Urban networks and network theory: the city as the connector of multiple networks. Urban Stud 47(13):2723–2735
Rodgers JL, Nicewander WA (1988) Thirteen ways to look at the correlation coefficient. Am Stat 42(1):59–66
Smith BL, Williams BM, Keith Oswald R (2002) Comparison of parametric and nonparametric models for traffic flow forecasting. Transp Res Part C Emerg Technol 10(4):303–321
Soper HE, Young AW, Cave BM, Lee A, Pearson K (1917) On the distribution of the correlation coefficient in small samples. Appendix II to the papers of “Student” and R. A. Fisher. A co-operative study. Biometrika 11(4):328–413
Stetzer F (1982) Specifying weights in spatial forecasting models: the results of some experiments. Env and Plan A 14(5):571–584
van Lint JWC, Hoogendoorn SP, van Zuylen HJ (2005) Accurate freeway travel time prediction with state-space neural networks under missing data. Transp Res Part C Emerg Technol 13(5–6):347–369
Vlahogianni EI, Golias JC, Karlaftis MG (2004) Short-term traffic forecasting: overview of objectives and methods. Transp Rev A Transnatl Transdisciplinary J 24(5):533–557
Wang J, Cheng T, Heydecker BG, Haworth J (2010) STARIMA for journey time prediction in London. In: Heydecker BG (ed) Proceedings of the 5th IMA conference on math in transp
Watts DJ, Strogatz SH (1998) Collective dynamics of “small-world” networks. Nature 393(6684):440–442
Williams BM, Hoel LA (2003) Modeling and forecasting vehicular traffic flow as a seasonal ARIMA process: theoretical basis and empirical results. J Transp Eng ASCE 129(6):664–672
Wu C, Ho J, Lee D (2004) Travel-time prediction with support vector regression. IEEE Trans Intell Transp Sys 5(4):276–281
Xu Z, Sui DZ (2007) Small-world characteristics on transportation networks: a perspective from network autocorrelation. J Geogr Syst 9(2):189–205