Fuzzy spatial models

Terry D. Clark, Jennifer M. Larson, John N. Mordeson, Joshua D. Potter, Mark J. Wierman

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Most political issues are more than one-dimensional in scope. For example, budget bills contain funding across a number of issue areas, and political parties engaged in cabinet formation must concern themselves with several issue dimensions in determining a government program capable of uniting a legislative majority. Hence, spatial models must incorporate n > 1 dimensions to be useful. Unfortunately, increasing the space to include multiple dimensions opens the possibility of cycling. The conditions under which cycling can occur have been the object of study for decades, and the conclusion is that the possibility of cycling is pervasive. Plott (1967), for instance, found that a maximal set exists in two-dimensional space only when ideal points are arrayed symmetrically to one another (the radial symmetry condition); and McKelvey (1976) found that in the absence of a maximal set, cycling is possible over the entire two-dimensional space. In order to reduce the likelihood of cycling, scholars have adopted increasingly restrictive assumptions in their models. While this has permitted the models to predict outcomes, increasingly restrictive assumptions remove the models further from reality, and empirical tests have often falsified the predictions. As a consequence, formal models have come under increasing criticism for the gap between their predictions and their empirical implications. The empirical implications in theoretical models (EITM) movement is one reflection of these criticisms (see Achen et al., 2002; De Marchi, 2005).

Original languageEnglish
Title of host publicationApplying Fuzzy Mathematics to Formal Models in Comparative Politics
Pages109-135
Number of pages27
Volume225
DOIs
StatePublished - 2008

Publication series

NameStudies in Fuzziness and Soft Computing
Volume225
ISSN (Print)14349922

Fingerprint

Spatial Model
Cycling
Fuzzy Model
Radial Symmetry
Prediction
Formal Model
Theoretical Model
Likelihood
Entire
Model
Predict

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Computational Mathematics

Cite this

Clark, T. D., Larson, J. M., Mordeson, J. N., Potter, J. D., & Wierman, M. J. (2008). Fuzzy spatial models. In Applying Fuzzy Mathematics to Formal Models in Comparative Politics (Vol. 225, pp. 109-135). (Studies in Fuzziness and Soft Computing; Vol. 225). https://doi.org/10.1007/978-3-540-77461-7_5

Fuzzy spatial models. / Clark, Terry D.; Larson, Jennifer M.; Mordeson, John N.; Potter, Joshua D.; Wierman, Mark J.

Applying Fuzzy Mathematics to Formal Models in Comparative Politics. Vol. 225 2008. p. 109-135 (Studies in Fuzziness and Soft Computing; Vol. 225).

Research output: Chapter in Book/Report/Conference proceedingChapter

Clark, TD, Larson, JM, Mordeson, JN, Potter, JD & Wierman, MJ 2008, Fuzzy spatial models. in Applying Fuzzy Mathematics to Formal Models in Comparative Politics. vol. 225, Studies in Fuzziness and Soft Computing, vol. 225, pp. 109-135. https://doi.org/10.1007/978-3-540-77461-7_5
Clark TD, Larson JM, Mordeson JN, Potter JD, Wierman MJ. Fuzzy spatial models. In Applying Fuzzy Mathematics to Formal Models in Comparative Politics. Vol. 225. 2008. p. 109-135. (Studies in Fuzziness and Soft Computing). https://doi.org/10.1007/978-3-540-77461-7_5
Clark, Terry D. ; Larson, Jennifer M. ; Mordeson, John N. ; Potter, Joshua D. ; Wierman, Mark J. / Fuzzy spatial models. Applying Fuzzy Mathematics to Formal Models in Comparative Politics. Vol. 225 2008. pp. 109-135 (Studies in Fuzziness and Soft Computing).
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