On the density distribution across space: a probabilistic approach

Ilenia Epifani () and Rosella Nicolini

UFAE and IAE Working Papers from Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC)

Abstract: This paper aims at providing a Bayesian parametric framework to tackle the accessibility problem across space in urban theory. Adopting continuous variables in a probabilistic setting we are able to associate with the distribution density to the Kendall's tau index and replicate the general issues related to the role of proximity in a more general context. In addition, by referring to the Beta and Gamma distribution, we are able to introduce a differentiation feature in each spatial unit without incurring in any a-priori definition of territorial units. We are also providing an empirical application of our theoretical setting to study the density distribution of the population across Massachusetts.

Keywords: Agglomerations; Bayesian inference; Distance; Gibbs sampling; Kendall's tau index; Population density. (search for similar items in EconPapers)
JEL-codes: C40 R14 (search for similar items in EconPapers)
Pages: 29
Date: 2009-07-22
New Economics Papers: this item is included in nep-ecm, nep-geo, nep-mic and nep-ure
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Related works:
Working Paper: On the density distribution across space: a probabilistic approach (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:aub:autbar:776.09

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