A minimum information principle

Snickars, Folke; Weibull, Jörgen W.

doi:10.1016/0166-0462(77)90021-7

Cited by 206 publications

(55 citation statements)

References 15 publications

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“…Zavedením omezení do výchozí situace pak dostáváme čtyři typy modelů prostorových interakcí (Wilson, 1974). Podobný přístup vycházející vždy z fyziky či matematiky zvolili i Snickars, Weibull (1977), Alonso (1978) a Tobler (1983. Teprve koncem 80. let 20. století byla opuštěna fyzikální inspirace pro modely prostorových interakcí (Fotheringham, O'Kelly, 1989; a posléze Fotheringham et al, 2000) a modelování interakcí vycházelo z behaviorálních přístupů, kdy se za základ považuje tzv.…”

Section: Modelování Prostorových Interakcí Gravitační Modelyunclassified

Časoprostorové modely nákupního chování české populace

Kunc¹,

Maryáš²,

Tonev³

et al. 2013

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Section: Modelování Prostorových Interakcí Gravitační Modelyunclassified

Časoprostorové modely nákupního chování české populace

Kunc¹,

Maryáš²,

Tonev³

et al. 2013

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“…At least, three theoretical foundations have been developed for this family of models: entropy maximisation, random utility, and finally models based on neurocomputing principles that represent a recent innovation in the design of spatial interaction models (Griffith, 1999;Fischer and Reggiani, forthcoming). Wilson (1970) introduced the entropy maximising theory supporting spatial interaction models, later extended by many others (see for example, Snickars and Weibull, 1977;Roy andLesse, 1981, andSmith, 1988). The fundamental assumption is that at the outset all outcomes are equally likely.…”

Section: Tendencies In Models and Methodsmentioning

confidence: 99%

The Theoretical and Methodological Toolbox of Urban Economics: From and Towards Where?

Capello¹,

Nijkamp²

2004

Urban Dynamics and Growth: Advances in Urban Economics

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“…Cross-entropy methods, such as Snickars and Weibull [31] (see also Golan and Vogel [32], Robinson et al [20] or Fernandez-Vasquez [33]), address the table update problem using a constrained optimization framework, in which the objective function is cross entropy [18]. That is, a Lagrangean is defined as some variation of:…”

Section: Proportional and Cross-entropy Methodsmentioning

confidence: 99%

A Bayesian Approach to the Balancing of Statistical Economic Data

Rodrigues

2014

Entropy

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Abstract:This paper addresses the problem of balancing statistical economic data, when data structure is arbitrary and both uncertainty estimates and a ranking of data quality are available. Using a Bayesian approach, the prior configuration is described as a multivariate random vector and the balanced posterior is obtained by application of relative entropy minimization. The paper shows that conventional data balancing methods, such as generalized least squares, weighted least squares and biproportional methods are particular cases of the general method described here. As a consequence, it is possible to determine the underlying assumptions and range of application of each traditional method. In particular, the popular biproportional method is found to assume that all source data has the same relative uncertainty. Finally, this paper proposes a simple linear iterative method that generalizes the biproportional method to the data balancing problem with arbitrary data structure, uncertainty estimates and multiple data quality levels.

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A minimum information principle

Cited by 206 publications

References 15 publications

Časoprostorové modely nákupního chování české populace

Časoprostorové modely nákupního chování české populace

The Theoretical and Methodological Toolbox of Urban Economics: From and Towards Where?

A Bayesian Approach to the Balancing of Statistical Economic Data

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