This preview shows page 1. Sign up to view the full content.
Unformatted text preview: STAT 333 Random Walk Summary The random walk is a Markov chain taking values in the integers S = { ..., 2 , 1 , , 1 , 2 ,... } . We assume that the walk starts at the origin 0 (that is, X = 0) although we may relabel the axis to make any chosen point the origin. On each step the process either jumps one unit to the right or one unit to the left. Therefore, we either have X n +1 = X n + 1 or X n +1 = X n 1 where X n = position of the walk after n steps. The jumps themselves (+ or ) can be viewed as a sequence of Bernoulli trials (or coin tosses) where p is the probability of a jump to the right (+) and q = 1 p is the probability of a jump to the left (). We assume that 0 < p < 1. • The event λ 0 0 = “return to 0” is a renewal event of period d = 2. • Let T 00 = number of steps to first return to 0. Then the probability of at least one return to 0 is f 0 0 = P ( T 00 < ∞ ) = 1  p q  ....
View
Full
Document
This note was uploaded on 07/12/2010 for the course STAT 333 taught by Professor Chisholm during the Winter '08 term at Waterloo.
 Winter '08
 Chisholm

Click to edit the document details