Modelling demand in restricted parking zones
Multiple linear regression (MLR) and geographically weighted regression (GWR) models are used for estimating parking demand in areas with paid short stay parking systems. These models have been applied to the city of Santander (Cantabria, Spain) to check their goodness of fit and their predictive ability. The results show the main advantages and disadvantages of using GWR models. The technique proved to be useful in this case study because it offered a better fit and made better predictions in a scenario showing a certain degree of spatial heterogeneity unexplained by any of the variables introduced into the global model. However, the GWR model also presented situations of local correlation although this was considered moderate given the results provided by the variance inflation factors and the local condition indexes.
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Volume (Year): 45 (2011)
Issue (Month): 6 (July)
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References listed on IDEAS
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- David C Wheeler, 2007. "Diagnostic tools and a remedial method for collinearity in geographically weighted regression," Environment and Planning A, Pion Ltd, London, vol. 39(10), pages 2464-2481, October.
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- Coro Chasco Yrigoyen, 2004. "Modelos De Heterogeneidad Espacial," Econometrics 0411004, EconWPA.
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- Bifulco, Gennaro Nicola, 1993. "A stochastic user equilibrium assignment model for the evaluation of parking policies," European Journal of Operational Research, Elsevier, vol. 71(2), pages 269-287, December.
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