Calibration Procedures and Problems of Stability in Nonlinear Dynamic Spatial Interaction Modeling

1986 ◽  
Vol 18 (3) ◽  
pp. 341-350 ◽  
Author(s):  
S T Lombardo ◽  
G A Rabino

The use of nonlinear dynamic spatial interaction models is one of the main approaches for the treatment of those phenomena of discontinuity and irreversibility which characterise the complexity of urban evolution. In this paper some methodological and operational problems which arise when a model of this kind, namely the Harris and Wilson model, is calibrated are dealt with. The main aspect of the calibration dealt with here is the problem of the separability of dynamics with different speeds (such as dynamics of stocks and dynamics of activities) when suitable data are lacking. It is shown, among other things, that a fundamental role is played by the intrinsic stability (or instability) of the equilibria of the model. The argument is illustrated by a set of simulations carried out on the Rome metropolitan area, relating to the retailing sector.


1998 ◽  
Vol 30 (8) ◽  
pp. 1497-1507 ◽  
Author(s):  
T J Fik ◽  
G F Mulligan

This paper is an examination of functional form and functional misspecification in regression-based spatial interaction models. Box–Cox transformations are used to model US state-to-state labor migration. Attention is given to the production-constrained gravity model, the competing and intervening destinations (CID) model, and an extension of the CID model which uses dummy variables and an iterative transformation procedure. Statistical evidence supports the argument that the use of highly restrictive log-linear specifications may be inappropriate and problematic. Implications for spatial interaction modeling using general nonrestrictive functional forms are discussed.



2020 ◽  
pp. 030913252096813
Author(s):  
Taylor M Oshan

Spatial interaction and spatial structure are foundational geographical abstractions, though there is often variation in how they are conceptualized and deployed in quantitative models. In particular, the last five decades have produced an exceptional diversity regarding the role of spatial structure within spatial interaction models. This is explored by outlining the initiation and development of the notion of spatial structure within spatial interaction modeling and critically reviewing four methodological approaches that emerged from ongoing debate about the topic. The outcome is a comprehensive coverage of the past and a sketch of one potential path forward for advancing this long-standing inquiry.



2020 ◽  
Author(s):  
Taylor M. Oshan

Spatial interaction and spatial structure are foundational geographical abstractions, though there is often variation in how they are conceptualized and deployed in quantitative models. In particular, the last five decades have produced an exceptional diversity regarding the role of spatial structure within spatial interaction models. This is explored by outlining the initiation and development of the notion of spatial structure within spatial interaction modeling and critically reviewing four methodological approaches that emerged from ongoing debate about the topic. The outcome is a comprehensive coverage of the past and a sketch of one potential path forward for advancing this longstanding inquiry.



1981 ◽  
Vol 13 (2) ◽  
pp. 217-224 ◽  
Author(s):  
J Ledent

This paper compares the system of equations underlying Alonso's theory of movement with that of Wilson's standard family of spatial-interaction models. It is shown that the Alonso model is equivalent to one of Wilson's four standard models depending on the assumption at the outset about which of the total outflows and/or inflows are known. This result turns out to supersede earlier findings—inconsistent only in appearance—which were derived independently by Wilson and Ledent. In addition to this, an original contribution of this paper—obtained as a byproduct of the process leading to the aforementioned result—is to provide an exact methodology permitting one to solve the Alonso model for each possible choice of the input data.



2013 ◽  
Vol 15 (3) ◽  
pp. 249-264 ◽  
Author(s):  
Giuseppe Arbia ◽  
Francesca Petrarca




REGION ◽  
2016 ◽  
Vol 3 (2) ◽  
pp. 11 ◽  
Author(s):  
Taylor M Oshan

This primer provides a practical guide to get started with spatial interaction modeling using the SpInt module in the python spatial analysis library (PySAL).



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