Missing data can lead to biased and inefficient estimation if the missing mechanism is not taken into account in the analysis. In this dissertation we propose two estimators that, under fairly general conditions, are asymptotically unbiased. The first proposed estimator assume the data are missing at random (MAR) and does...
This thesis contains three manuscripts addressing the application of stochastic processes to the analysis and solution of partial differential equations (PDEs) in mathematical physics.
In the first manuscript, one dimensional diffusion and Burgers equation are considered. The Fourier transform of the solution to each PDE is represented as the expected...