Spatial-temporal data arises in many applications, for example, environment sciences and disease mapping. This dissertation focuses on Gaussian spatial-temporal data. To make statistical inference for Gaussian spatial-temporal data, we developed a special class of spatial-temporal Gaussian state-space models in which the state vectors are constructed following spatial-temporal Gaussian autoregressions that...
Linear solvers are often used to solve neutron diffusion problems. These tools have two significant shortcomings. First, parallel implementations provide only a modest speedup. The operations cannot be divided cleanly between processors. Second, for large matrices they can be very slow. Our primary goal is to find a new method...
One of the ways of countering the ever increasing computational requirements in the simulation and modeling of electrical and electromagnetic devices and phenomena, is the development of simulation and modeling tools on parallel computing platforms. In this thesis, a previously developed Monte Carlo parallel device simulator is utilized, enhanced, and...