Outputs (5)

Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches (2021)
Book Chapter
Errington, A., Einbeck, J., & Cumming, J. (2021). Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches. In M. Vasile, & D. Quagliarella (Eds.), Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications (393-405). Springer Verlag. https://doi.org/10.1007/978-3-030-80542-5_24

If individuals are exposed to ionising radiation, due to some radiation accident, for medical reasons, or during spaceflight, there is often a need to estimate the contracted radiation dose. The field of biodosimetry is concerned with estimating the... Read More about Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches.

Uncertainty Quantification in Lasso-Type Regularization Problems (2020)
Book Chapter
Basu, T., Einbeck, J., & Troffaes, M. C. (2021). Uncertainty Quantification in Lasso-Type Regularization Problems. In Optimization Under Uncertainty with Applications to Aerospace Engineering (81-109). Springer Verlag. https://doi.org/10.1007/978-3-030-60166-9_3

On the Use of Random Effect Models for Radiation Biodosimetry (2017)
Book Chapter
Einbeck, J., Ainsbury, E., Barnard, S., Oliveira, M., Manning, G., Puig, P., & Badie, C. (2017). On the Use of Random Effect Models for Radiation Biodosimetry. In E. Ainsbury, M. Calle, E. Cardis, J. Einbeck, G. Gómez, & P. Puig (Eds.), Extended abstracts Fall 2015 : Biomedical Big Data ; Statistics for Low Dose Radiation Research (89-94). Springer Verlag. https://doi.org/10.1007/978-3-319-55639-0_15

The application of random effect models to different radiation biomarkers, including cytogenetic, protein-based, and gene-expression based biomarkers, is discussed. Explicit case studies are provided for the latter two scenarios, in which random effe... Read More about On the Use of Random Effect Models for Radiation Biodosimetry.

Hotspots in Hindsight (2015)
Book Chapter
Julian, B., Foulger, G., Hatfield, O., Jackson, S., Simpson, E., Einbeck, J., & Moore, A. (2015). Hotspots in Hindsight. In G. Foulger, M. Lustrino, & S. King (Eds.), The Interdisciplinary Earth: A Volume in Honor of Don L. Anderson (105-121). The Geological Society of America / AGU. https://doi.org/10.1130/2015.2514%2808%29

Several workers have suggested that the locations of melting anomalies (hotspots) and the original locations of large igneous provinces (LIPs) and kimberlite pipes lie preferentially above the margins of two large low-shear-velocity provinces, or LLS... Read More about Hotspots in Hindsight.

Representing complex data using localized principal components with application to astronomical data. (2008)
Book Chapter
Einbeck, J., Evers, L., & Bailer-Jones, C. (2008). Representing complex data using localized principal components with application to astronomical data. In A. Gorban, B. Kegl, D. Wunsch, & A. Zinovyev (Eds.), Lecture Notes in Computational Science and Engineering (180-204). Springer Verlag. https://doi.org/10.1007/978-3-540-73750-6_7

Often the relation between the variables constituting a multivariate data space might be characterized by one or more of the terms: ``nonlinear'', ``branched'', ``disconnected'', ``bended'', ``curved'', ``heterogeneous'', or, more general, ``complex'... Read More about Representing complex data using localized principal components with application to astronomical data..