Mark A. Thyer

Water Science and Technology · 2006–2017

A researcher in the Science corpus: 5 papers; trusts 19 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Water Science and Technology — 44 citations into it; #82 of 1,711 by trust here, #317 by citations
• Global and Planetary Change — 41 citations into it; #771 of 10,225 by trust here, #1,759 by citations
• Environmental Engineering — 26 citations into it
• Artificial Intelligence — 6 citations into it
• Ocean Engineering — 6 citations into it
• Atmospheric Science — 5 citations into it
• Finance — 5 citations into it

Whom Mark A. Thyer trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Dmitri Kavetski
2. George A. Kuczera
3. Keith Beven
4. Boris G. Mirkin
5. Tilmann Gneiting
6. S. Franks
7. Quan J. Wang
8. Francesco Laio
9. A. Binley
10. M. Clark

Who trusts Mark A. Thyer overall

1. Dmitri Kavetski
2. Keith Beven
3. Jasper A. Vrugt
4. G. Schoups
5. Quan J. Wang
6. Benjamin Renard
7. David McInerney
8. M. Clark
9. Zhangjun Liu
10. George A. Kuczera

Papers from Mark A. Thyer's perspective

Ordered by how strongly the researchers Mark A. Thyer trusts endorse each paper. Same corpus, a different order for every researcher.

1. Critical evaluation of parameter consistency and predictive uncertainty in hydrological modeling: A case study using Bayesian total error analysis
2. The future of distributed models: model calibration and uncertainty prediction.
3. Bayesian calibration of computer models
4. Hydrological forecasting uncertainty assessment: Incoherence of the GLUE methodology
5. A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non‐Gaussian errors
6. Multi-model ensemble hydrologic prediction using Bayesian model averaging
7. Probabilistic forecasts, calibration and sharpness
8. An integrated hydrologic Bayesian multimodel combination framework: Confronting input, parameter, and model structural uncertainty in hydrologic prediction
9. Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterising model error using storm-dependent parameters
10. An Analysis of Transformations

Their papers

• Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modeling heteroscedastic residual errors (2017) — 142 citations
• Comparison of joint versus postprocessor approaches for hydrological uncertainty estimation accounting for error autocorrelation and heteroscedasticity (2014) — 156 citations
• Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors (2010) — 825 citations
• Critical evaluation of parameter consistency and predictive uncertainty in hydrological modeling: A case study using Bayesian total error analysis (2009) — 394 citations
• Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterising model error using storm-dependent parameters (2006) — 378 citations