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Kleiber, William Paul Assistant Professor

Positions

Research Areas research areas

Research

research overview

  • Dr. Kleiber is an expert in spatial statistics, developing theory for multivariate space-time processes, including flexible nonstationary models as well as feasible estimation approaches for large datasets. Dr. Kleiber also has expertise in computer experiments, and has developed methodological approaches for calibrating, emulating and analyzing complex geophysical computer models. Another primary focus is statistical climatology, especially in building stochastic weather simulators for use in agricultural, ecological and hydrological modeling. He has also developed approaches for probabilistic weather forecasting, focusing on sharp and calibrated local forecasting for temperature and precipitation. Recent research has focused on stochastic parameterizations and stochastic modeling for energy applications.

keywords

  • spatial statistics, matrix-valued positive definite functions, covariance functions, stochastic modeling, geostatistics, Gaussian processes, computer experiments, nonstationarity, space-time processes, model calibration, model emulation, large datasets, stochastic weather generators

Publications

selected publications

Teaching

courses taught

  • APPM 4550 Spatial Statistics (Spring 2019)
  • APPM 4580 Statistical Learning (Spring 2019)
  • APPM 4840 Reading and Research in Applied Mathematics (Spring 2019)
  • APPM 5550 Spatial Statistics (Spring 2019)
  • APPM 5580 Introduction to Statistical Learning (Spring 2019)
  • APPM 6950 Master's Thesis (Spring 2019)
  • APPM 8990 Doctoral Dissertation (Spring 2019)
  • APPM 6950 Master's Thesis (Fall 2018)
  • APPM 8990 Doctoral Dissertation (Fall 2018)
  • APPM 6950 Master's Thesis (Summer 2018)
  • APPM 8990 Doctoral Dissertation (Summer 2018)
  • APPM 4540 Introduction to Time Series (Spring 2018)
  • APPM 4580 Statistical Learning (Spring 2018)
  • APPM 4840 Reading and Research in Applied Mathematics (Spring 2018)
  • APPM 5540 Introduction to Time Series (Spring 2018)
  • APPM 5580 Introduction to Statistical Learning (Spring 2018)
  • APPM 6950 Master's Thesis (Spring 2018)
  • APPM 8990 Doctoral Dissertation (Spring 2018)
  • MATH 4540 Introduction to Time Series (Spring 2018)
  • MATH 5540 Introduction to Time Series (Spring 2018)

Background

International Activities

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