## Masters Theses & Specialist Projects

#### Publication Date

5-2015

Dr. David Neal (Director), Dr. Ngoc Nguyen, and Dr. Lan Nguyen

#### Degree Program

Department of Mathematics

#### Degree Type

Master of Science

#### Abstract

This thesis provides a study of various boundary problems for one and two dimensional random walks. We first consider a one-dimensional random walk that starts at integer-valued height k > 0, with a lower boundary being the x-axis, and on each step moving downward with probability q being greater than or equal to the probability of going upward p. We derive the variance and the standard deviation of the number of steps T needed for the height to reach 0 from k, by first deriving the moment generating function of T. We then study two types of two-dimensional random walks with four boundaries. A Type I walk starts at integer-valued coordinates (h; k), where0 < h < m and 0 < k < n. On each step, the process moves one unit either up, down, left, or right with positive probabilities pu, pd, pl, pr, respectively, where pu + pd + pl + pr = 1. The process stops when it hits a boundary. A Type II walk is similar to a Type I walk except that on each step, the walk moves diagonally, either left and upward, left and downward, right and downward, or right and upward with positive probabilities plu, pld, prd, pru, respectively. We mainly answer two questions on these two types of two-dimensional random walks: (1) What is the probability of hitting one boundary before the others from an initial starting point? (2) What is the average number of steps needed to hit a boundary? To do so, we introduce a Markov Chains method and a System of Equations method. We then apply the obtained results to a boundary problem involving two independent one-dimensional random walks and answer various questions that arise. Finally, we develop a conjecture to calculate the probability of a two-sided downward-drifting Type II walk with even-valued starting coordinates hitting the x-axis before the y-axis, and we test the result with Mathematica simulations

#### Disciplines

Applied Mathematics | Mathematics | Probability

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