Cookies?
Library Header Image
LSE Research Online LSE Library Services

Embracing equifinality with efficiency : limits of acceptability sampling using the DREAM(LOA) algorithm

Vrugt, Jasper A. and Beven, Keith J. (2018) Embracing equifinality with efficiency : limits of acceptability sampling using the DREAM(LOA) algorithm. Journal of Hydrology, 559. pp. 954-971. ISSN 0022-1694

[img]
Preview
Text - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (7MB) | Preview

Identification Number: 10.1016/j.jhydrol.2018.02.026

Abstract

This essay illustrates some recent developments to the DiffeRential Evolution Adaptive Metropolis (DREAM) MATLAB toolbox of Vrugt, 2016 to delineate and sample the behavioural solution space of set-theoretic likelihood functions used within the GLUE (Limits of Acceptability) framework (Beven and Binley, 1992; Beven and Freer, 2001; Beven, 2006; Beven et al., 2014). This work builds on the DREAM (ABC) algorithm of Sadegh and Vrugt, 2014 and enhances significantly the accuracy and CPU-efficiency of Bayesian inference with GLUE. In particular it is shown how lack of adequate sampling in the model space might lead to unjustified model rejection.

Item Type: Article
Official URL: https://www.sciencedirect.com/journal/journal-of-h...
Additional Information: © 2018 Elsevier B.V.
Divisions: Centre for Analysis of Time Series
Subjects: H Social Sciences > HA Statistics
Date Deposited: 19 Mar 2018 15:15
Last Modified: 11 Dec 2024 21:34
URI: http://eprints.lse.ac.uk/id/eprint/87291

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics