Bias and uncertainty in regression-calibrated models of groundwater flow in heterogeneous media
By R. L. Cooley, S. Christensen. 2006
49 citations recorded by the source corpus.
Subfields: Environmental Engineering, Geochemistry and Petrology
View Paper: https://www.semanticscholar.org/paper/d10f86beb2b25427fc8c0a2bb408fe2a6c42d060
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Environmental Engineering
- Jasper A. Vrugt
- M. Tonkin
- John Doherty
- Catherine R. Moore
- Qinjun Kang
- Elizabeth H. Keating
- Eric Laloy
- Thomas Wöhling
In Geochemistry and Petrology
- M. Tonkin
- Jasper A. Vrugt
- John Doherty
- Catherine R. Moore
- Qinjun Kang
- Elizabeth H. Keating
- Hoshin V. Gupta
- P. Pokhrel
Citations in the corpus
- Efficient nonlinear predictive error variance for highly parameterized models (2006, background): “For example, the bulk of measurement noise may be structural noise induced by model inadequacy and parameter simplifications [Cooley and Christensen, 2006].”
- Optimization and uncertainty assessment of strongly nonlinear groundwater models with high parameter dimensionality (2010, background): “For example, the assumption that measurement/structural noise is uncorrelated, or even possesses a known and/or stationary covariance matrix, is almost never met [Cooley, 2004; Cooley and Christensen, 2006; Doherty and Welter, 2010].”