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A fish-based index of estuarine ecological quality incorporating information from both scientific fish survey and experts knowledge ArchiMer
Tableau, Adrien; Drouineau, Hilaire; Delpech, C.; Pierre, M.; Lobry, J.; Le Pape, O.; Breine, J.; Lepage, Mario.
In the Water Framework Directive (European Union) context, a multimetric fish based index is required to assess the ecological status of French estuarine water bodies. A first indicator called ELFI was developed, however similarly to most indicators, the method to combine the core metrics was rather subjective and this indicator does not provide uncertainty assessment. Recently, a Bayesian method to build indicators was developed and appeared relevant to select metrics sensitive to global anthropogenic pressure, to combine them objectively in an index and to provide a measure of uncertainty around the diagnostic. Moreover, the Bayesian framework is especially well adapted to integrate knowledge and information not included in surveys data. In this context,...
Tipo: Text Palavras-chave: Anthropogenic pressure; Bayesian method; Expert judgement; Multimetric fish-based indicator; Prior information; Water Framework Directive.
Ano: 2013 URL: http://archimer.ifremer.fr/doc/00146/25700/24029.pdf
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Bayesian estimation of non-stationary Markov models combining micro and macro data AgEcon
Storm, Hugo; Heckelei, Thomas.
In this poster a Bayesian estimation framework for a non-stationary Markov model is developed for situations where sample data with observed transition between classes (micro data) and aggregate population shares (macro data) are available. Posterior distributions on transition probabilities are derived based on a micro based prior and a macro based Likelihood function thereby consistently combining previously separated approaches. Monte Carlo simulations for ordered and unordered Markov states show how observed micro transitions improve precision of posterior knowledge as the sample size increases.
Tipo: Conference Paper or Presentation Palavras-chave: Bayesian estimation; Markov transitions; Prior information; Multinomial logit; Ordered multinomial logit; Agricultural and Food Policy; Research Methods/ Statistical Methods.
Ano: 2011 URL: http://purl.umn.edu/103645
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PARAMETER ESTIMATION FOR A COMPUTABLE GENERAL EQUILIBRIUM MODEL: A MAXIMUM ENTROPY APPROACH AgEcon
Arndt, Channing; Robinson, Sherman; Tarp, Finn.
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of nonlinear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints. Second, it permits incorporation of prior information on parameter values. Third, it can be applied in the absence of copious data. Finally, it supplies measures of the capacity of the model to reproduce the historical record and the statistical significance of parameter estimates. The method is applied to estimating a CGE model of Mozambique.
Tipo: Working or Discussion Paper Palavras-chave: Maximum entropy; Computable general equilibrium; CGE; Prior information; Mozambique.; Research Methods/ Statistical Methods; C51; C68.
Ano: 2001 URL: http://purl.umn.edu/42456
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