Dynamics of an Adaptive Randomly Reinforced Urn
Abstract
Adaptive randomly reinforced urn (ARRU) is a two-color urn model where the updating process is defined by a sequence of non-negative random vectors \(D1,n, D2,n);n≥1\ and randomly evolving thresholds which utilize accruing statistical information for the updates. Let m1=E[D1,n] and m2=E[D2,n]. Motivated by applications, in this paper we undertake a detailed study of the dynamics of the ARRU model. First, for the case m1 ≠ m2, we establish L1 bounds on the increments of the urn proportion at fixed and increasing times under very weak assumptions on the random threshold sequence. As a consequence, we deduce weak consistency of the evolving urn proportions. Second, under slightly stronger conditions, we establish the strong consistency of the urn proportions for all finite values of m1 and m2. Specifically, we show that when m1=m2 the proportion converges to a non-degenerate random variable. Third, we establish the asymptotic distribution, after appropriate centering and scaling, of the proportion of sampled balls in the case m1=m2. In the process, we settle the issue of asymptotic distribution of the number of sampled balls for a randomly reinforced urn (RRU). To address the technical issues, we establish results on the harmonic moments of the total number of balls in the urn at different times under very weak conditions, which is of independent interest.
Turn this paper into a lesson
ArcXiv compiles a structured reading guide from this paper's metadata: plain-English importance, contributions, prerequisite concepts, which sections to read first, flashcards, and a quiz. Grounded in the abstract, never invented.