Richard A. Davis

Short CV

Richard Davis received his B.A. and Ph.D. degree in mathematics in1974 and 1979 from University of California at San Diego, where he studied under the direction of Professor Murray Rosenblatt. He spent two years, 1979-1981, as an Instructor in Applied Mathematics at Massachusetts Institute of Technology (MIT) before joining Colorado State University (CSU) as an Assistant Professor in Statistics. From 1990 he was Professor at the Department of Statistics at CSU. After spending 26 years at CSU, Davis joined the Statistics Department at Columbia University in 2007.Davis has also held visiting appointments at several institutions, including the Center for Stochastic Processes at University of North Carolina, University of California at San Diego, University of New South Wales, and the Melbourne Institute of Technology. Davis is fellow of the Institute of Mathematical Statistics and the American Statistical Association, and he is an elected member of the International Statistical Institute. He also acts as the Co-director of Program for Interdisciplinary Mathematics, Ecology and Statistics (PRIMES), an NSF IGERT funded project at CSU.


Selected Awards

  • 2006, Professor Laureate, College of Natural Sciences, Colorado State University
  • 2003, IBM Faculty Award
  • 2001, Environmental Protection Agency-STAR grant
  • 1998, Koopmans Prize for Econometric Theory
  • 1986, Alumni Faculty of the Year, CSU, College of Natural Sciences

Research Interests

Davis’ research interests lie primarily in the areas of applied probability, time series, and stochastic processes. His dissertation work focused on extreme values of general stationary processes. While his research interests have gravitated towards problems in time series analysis (inference, estimation, prediction and general properties of time series models), extreme value theory still has a strong influence in his approach to solving problems.


Selected Publications

  • Andrews, Beth; Davis, Richard A.; Breidt, F. Jay: Rank-based estimation for all-pass time series models. Ann. Statist. 35 (2), 2007, 844-869.
  • Davis, Richard A; Lee, Thomas C. M; Rodriguez-Yam, Gabriel A: Structural Break Estimation for Nonstationary Time Series Models. Journal of the American Statistical Association 101 (473), 2006, 223-239.
  • Davis, R.A.; Brockwell, P.J.: Introduction to Time Series and Forecasting. Springer New York, 2002.
  • Breidt, F.J.; Trindade, A.; Davis, R.A.: Least absolute deviation estimation for all-pass time series models. Annals of Statistics 29, 2001, 919-946.
  • Basrak, B.; Mikosch, T.; Davis, R.A.: A characterization of multivariate regular variation. Annals of Applied Probability, 2001.
  • Davis, R.A.; Mikosch, T.: The sample ACF of heavy-tailed stationary processes with applications to ARCH. Annals of Statistics 26, 1998, 522-536.
  • Davis, Richard A.: Gauss-Newton and M-estimation for ARMA processes with infinite variance. Stochastic Processes and their Applications 63 (1), 1996, 75-95.
  • Dunsmuir, W.T.M.; Davis, R.A.: Maximum likelihood estimation for MA(1) processes with a root on or near the unit circle. Econometric Theory 12, 1996, 1-29.
  • Brockwell, Peter J.; Davis, Richard A.: Time Series: Theory and Methods. Springer New York, 1991.