Approximate Bayesian Computation using Markov Chain Monte Carlo simulation: DREAM(ABC)

Pitfalls and improvements in the joint inference of heteroscedasticity and autocorrelation in hydrological model calibration

(2013) Guillaume Evin et al.   WATER RESOURCES RESEARCH

Toward diagnostic model calibration and evaluation: Approximate Bayesian computation

(2013) Jasper A. Vrugt et al.   WATER RESOURCES RESEARCH

Approximate Bayesian Computation

(2013) Mikael Sunnåker et al.   PLoS Computational Biology

A tutorial on approximate Bayesian computation

(2012) Brandon M. Turner et al.   JOURNAL OF MATHEMATICAL PSYCHOLOGY

Approximate Bayesian computation with differential evolution

(2012) Brandon M. Turner et al.   JOURNAL OF MATHEMATICAL PSYCHOLOGY

Generalized likelihood uncertainty estimation (GLUE) and approximate Bayesian computation: What's the connection?

(2012) David J. Nott et al.   WATER RESOURCES RESEARCH

Accelerating Markov Chain Monte Carlo Simulation by Differential Evolution with Self-Adaptive Randomized Subspace Sampling

(2011) J. A. Vrugt et al.   INTERNATIONAL JOURNAL OF NONLINEAR SCIENCES AND NUMERICAL SIMULATION

An adaptive sequential Monte Carlo method for approximate Bayesian computation

(2011) Pierre Del Moral et al.   STATISTICS AND COMPUTING

High-dimensional posterior exploration of hydrologic models using multiple-try DREAM(ZS) and high-performance computing

(2011) Eric Laloy et al.   WATER RESOURCES RESEARCH

Approximate Bayesian Computation in Evolution and Ecology

(2010) Mark A. Beaumont   Annual Review of Ecology Evolution and Systematics

ABC as a flexible framework to estimate demography over space and time: some cons, many pros

(2010) G. BERTORELLE et al.   MOLECULAR ECOLOGY

Approximate Bayesian Computation (ABC) in practice

(2010) Katalin Csilléry et al.   TRENDS IN ECOLOGY & EVOLUTION

Ancient numerical daemons of conceptual hydrological modeling: 2. Impact of time stepping schemes on model analysis and prediction

(2010) Dmitri Kavetski et al.   WATER RESOURCES RESEARCH

A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non-Gaussian errors

(2010) Gerrit Schoups et al.   WATER RESOURCES RESEARCH

Ancient numerical daemons of conceptual hydrological modeling: 1. Fidelity and efficiency of time stepping schemes

(2010) Martyn P. Clark et al.   WATER RESOURCES RESEARCH

Development of a formal likelihood function for improved Bayesian inference of ephemeral catchments

(2010) Tyler Smith et al.   WATER RESOURCES RESEARCH

Efficient Approximate Bayesian Computation Coupled With Markov Chain Monte Carlo Without Likelihood

(2009) Daniel Wegmann et al.   GENETICS

Model criticism based on likelihood-free inference, with an application to protein network evolution

(2009) O. Ratmann et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Non-linear regression models for Approximate Bayesian Computation

(2009) Michael G. B. Blum et al.   STATISTICS AND COMPUTING

Reconciling theory with observations: elements of a diagnostic approach to model evaluation

(2008) Hoshin V. Gupta et al.   HYDROLOGICAL PROCESSES

Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems

(2008) T. Toni et al.   Journal of the Royal Society Interface

Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation

(2008) Jasper A. Vrugt et al.   WATER RESOURCES RESEARCH