Associate Professor,
Department of Statistics,
Carnegie Mellon University
Ph.D., University of California, Berkeley
A description, along with documented code, of the procedure I developed for constructing minimax expected size and minimax regret confidence procedures.
I am a member of the International Computational Astrostatistics (INCA) Group.
I was a member of a small group that developed the Fast Ocean Atmosphere Model (FOAM). The model has enjoyed wide use; see related publications.
I am affiliated with the McWilliams Center for Cosmology and the Center for the Study and Improvement of Regulation.
"Constructing Confidence Regions of Optimal Expected Size."
Schafer, C. and P. Stark. (2009)
Journal of the American Statistical Association.
(104): 1080-1089.
"High-dimensional Density Estimation via SCA: An Example in the Modelling of Hurricane Tracks"
Buchman, S., A. Lee, and C. Schafer (2009)
To appear in Statistical Methodology.
"Accurate Parameter Estimation for Star Formation History in Galaxies using SDSS Spectra."
Richards, J., P. Freeman, A. Lee, and C. Schafer. (2009)
Monthly Notices of the Royal Astronomical Society. (399): 1044-1057.
"Photometric Redshift Estimation Using SCA."
Freeman, P., J. Newman, A. Lee, J. Richards, and C. Schafer. (2009)
Monthly Notices of the Royal Astronomical Society. (398): 2012-2021.
"Exploiting Low-Dimensional Structure in Astronomical Spectra."
Richards, J., P. Freeman, A. Lee, and C. Schafer. (2009)
The Astrophysical Journal. (691): 32-42.
"Selecting Local Models in Multiple Regression by Maximizing Power."
Schafer, C. and K. Doksum. (2009)
Metrika. (69): 283-304.
"Astrostatistics: The Final Frontier."
Freeman, P., J. Richards, C. Schafer, and A. Lee. (2008)
Chance. (21).
"A Statistical Method for Estimating Luminosity Functions using Truncated Data."
Schafer, C. (2007)
The Astrophysical Journal. (661): 703-713.
"Efficiently Computing Minimax Expected-Size Confidence Regions."
Bryan, B., H. McMahan, C. Schafer, and J. Schneider. (2007)
Accepted paper for International Conference on Machine Learning.
"Powerful Choices: Tuning Parameter Selection Based on Power."
Doksum, K. and C. Schafer. (2006)
In Frontiers in Statistics. Fan, J. and H. Koul, editors. 113-141.
"Using What we Know: Inference with Physical Constraints."
Schafer, C. and P. Stark. (2003)
Statistical Problems in Particle Physics, Astrophysics, and Cosmology. 25-34.
"Computational Design and Performance of the Fast Ocean Atmosphere
Model, Version One."
Jacob, R., C. Schafer, I. Foster, M. Tobis, and J. Anderson. (2001)
Proc. 2001 International Conference on
Computational Science. Alexandrov, V., J. Dongarra, C. Tan, editors.
Springer-Verlag. Also ANL/CGC-005-0401, April 2001.
"FOAM: Expanding the Horizons of Climate Modeling."
Tobis, M., I. Foster, C. Schafer, R. Jacob, and J. Anderson. (1997)
Technical Paper,
SC97:High Performance Networking and Computing.
"Exploring Coupled Atmosphere-Ocean Models Using (Vis5D)."
Hibbard, W., J. Anderson, I. Foster, B. Paul, R. Jacob, C. Schafer, and
M. Tyree. (1996)
International Journal of Supercomputer Applications. (10): 211-222.
36-752, Advanced Probability Overview.
36-410, Introduction to Probability Models.
36-247, Statistics for the Lab Sciences.