Correlations between parameters in risk models : estimation and propagation of uncertainty by Markov Chain Monte Carlo
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003 | MAP | ||
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100 | 1 | $0MAPA20080018849$aAdes, A. E. | |
245 | 1 | 0 | $aCorrelations between parameters in risk models$b: estimation and propagation of uncertainty by Markov Chain Monte Carlo$cA. E. Ades and G. Lu |
520 | 8 | $aMonte Carlo simulation has become the accepted method for propagating parameter uncertainty through risk models. It is widely appreciated, however, that correlations between input variables must be taken into account if models are to deliver correct assessments of uncertainty in risk | |
650 | 1 | 1 | $0MAPA20080608606$aSimulación Monte Carlo |
650 | 1 | 1 | $0MAPA20080546878$aDioxinas |
650 | 1 | 1 | $0MAPA20080589004$aAnálisis matemático |
650 | 0 | 1 | $0MAPA20080601522$aEvaluación de riesgos |
650 | 1 | 1 | $0MAPA20080610319$aDistribución de riesgos |
650 | 1 | $0MAPA20080602642$aModelos de simulación | |
700 | 1 | $0MAPA20080000417$aLu, G. | |
773 | 0 | $wMAP20077000345$tRisk analysis : an international journal$dNew York and London : Society for Risk Analysis$gVol. 23, nº 6, December, 2003 ; p. 1165-1172 |