Title: DEPENDENCE BETWEEN PATH-LENGTH AND SIZE IN RANDOM DIGITAL TREES
Authors: Fuchs, Michael
Hwang, Hsien-Kuei
應用數學系
Department of Applied Mathematics
Keywords: Random tries;covariance;total path length;Pearson's correlation coefficient;asymptotic normality;Poissonization;de-Poissonization;integral transform;contraction method
Issue Date: 1-Dec-2017
Abstract: We study the size and the external path length of random tries and show that they are asymptotically independent in the asymmetric case but strongly dependent with small periodic fluctuations in the symmetric case. Such an unexpected behavior is in sharp contrast to the previously known results on random tries, that the size is totally positively correlated to the internal path length and that both tend to the same normal limit law. These two dependence examples provide concrete instances of bivariate normal distributions (as limit laws) whose components have correlation either zero or one or periodically oscillating. Moreover, the same type of behavior is also clarified for other classes of digital trees such as bucket digital trees and Patricia tries.
URI: http://dx.doi.org/10.1017/jpr.2017.56
http://hdl.handle.net/11536/144429
ISSN: 0021-9002
DOI: 10.1017/jpr.2017.56
Journal: JOURNAL OF APPLIED PROBABILITY
Volume: 54
Begin Page: 1125
End Page: 1143
Appears in Collections:Articles