Development of an indicator to assess the spatial fit of discrete choice models |
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| Institution: | 1. Human Potential Centre, Auckland University of Technology, Auckland, New Zealand;2. School of Nursing, The University of Auckland, Auckland, New Zealand;1. Fraunhofer Institute for Industrial Engineering IAO, Nobelstr. 12, 70569 Stuttgart, Germany;2. Fraunhofer Institute for Manufacturing Engineering and Automation IPA, Nobelstr. 12, 70569 Stuttgart, Germany;3. Fraunhofer Institute for Interfacial Engineering and Biotechnology IGB, Nobelstr. 12, 70569 Stuttgart, Germany;1. Key Lab of Data Engineering and Knowledge Engineering of MOE, Renmin University of China, Beijing, China;2. College of Computer and Information Engineering, Henan University, Kaifeng, China |
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| Abstract: | Discrete choice models are increasingly implemented using geographical data. When this is the case, it may not be sufficient to project market shares accurately, but also to correctly replicate the spatial pattern of choices. Analysts might then be interested in assessing the results of a model’s fit relative to the spatial distribution of the observed responses. While canonical approaches exist for the exploratory spatial analysis of continuous variables, similar tools have not been widely implemented for discrete choice models, where the variable of interest is categorical. For this reason, despite recent progress with spatial models for discrete outcomes, there is still not a simple and intuitive tool to assess the quality of the spatial fit of a discrete choice model. The objective of this paper is to introduce a new indicator of spatial fit that can be applied to the results of discrete choice models. Utility of the indicator is explored by means of numerical experiments and then demonstrated by means of a case study of vehicle ownership in Montreal, Canada. |
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| Keywords: | Discrete choice models Spatial analysis Spatial fit Auto ownership Montreal |
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