In this section
@article{Hilton:2019,
author = {Hilton, B and Sood, AP and Evans, TS},
journal = {Scientific Reports},
title = {Predictive limitations of spatial interaction models: a non-Gaussian analysis},
url = {http://arxiv.org/abs/1909.07194v1},
year = {2019}
}
TY - JOUR
AB - We present a method to compare spatial interaction models against data basedon well known statistical measures which are appropriate for such models anddata. We illustrate our approach using a widely used example: commuting data,specifically from the US Census 2000. We find that the radiation model performssignificantly worse than an appropriately chosen simple gravity model. Variousconclusions are made regarding the development and use of spatial interactionmodels, including: that spatial interaction models fit badly to data in anabsolute sense, that therefore the risk of over-fitting is small and addingadditional fitted parameters improves the predictive power of models, and thatappropriate choices of input data can improve model fit.
AU - Hilton,B
AU - Sood,AP
AU - Evans,TS
PY - 2019///
SN - 2045-2322
TI - Predictive limitations of spatial interaction models: a non-Gaussian analysis
T2 - Scientific Reports
UR - http://arxiv.org/abs/1909.07194v1
UR - http://hdl.handle.net/10044/1/73833
ER -