On Weighted Depths in Random Binary Search Trees

Rafik Aguech (), Anis Amri () and Henning Sulzbach ()
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Rafik Aguech: King Saud University
Anis Amri: University of Monastir
Henning Sulzbach: University of Birmingham, School of Mathematics

Journal of Theoretical Probability, 2018, vol. 31, issue 4, 1929-1951

Abstract: Abstract Following the model introduced by Aguech et al. (Probab Eng Inf Sci 21:133–141, 2007), the weighted depth of a node in a labelled rooted tree is the sum of all labels on the path connecting the node to the root. We analyse weighted depths of nodes with given labels, the last inserted node, nodes ordered as visited by the depth first search process, the weighted path length and the weighted Wiener index in a random binary search tree. We establish three regimes of nodes depending on whether the second-order behaviour of their weighted depths follows from fluctuations of the keys on the path, the depth of the nodes or both. Finally, we investigate a random distribution function on the unit interval arising as scaling limit for weighted depths of nodes with at most one child.

Keywords: Analysis of algorithm; Data structures; Binary search trees; Central limit theorems; Contraction method; Random probability measures; 60F05; 68P05; 68Q25 (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s10959-017-0773-1

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