For the perimeter length Ln and the area An of the convex hull of the first n steps of a planar random walk, this thesis study n -> ∞ mean and variance asymptotics and establish distributional limits. The results apply to random walks both with drift (the mean of random walk increments) and with no drift under mild moments assumptions on the increments. Assuming increments of the random walk have finite second moment and non-zero mean, Snyder and Steele showed that n−1Ln converges almost surely to a deterministic limit, and proved an upper bound on the variance Var[Ln] = O(n). We show that n−1Var[Ln] converges and give a simple expression for the limit,which is non-zero for walks outside a certain degenerate class. This answers a question of Snyder and Steele. Furthermore, we prove a central limit theorem for Ln in the non-degenerate case. Then we focus on the perimeter length with no drift and area with both drift and zero-drift cases. These results complement and contrast with previous work and establish non-Gaussian distributional limits. We deduce these results from weak convergence statements for the convex hulls of random walks to scaling limits defined in terms of convex hulls of certain Brownian motions. We give bounds that confirm that the limiting variances in our results are non-zero.
|Date of Award||18 May 2017|
- University Of Strathclyde
|Sponsors||EPSRC (Engineering and Physical Sciences Research Council) & University of Strathclyde|
|Supervisor||Xuerong Mao (Supervisor) & Andrew Wade (Supervisor)|