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.
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