Fragmentation of Random Trees
نویسندگان
چکیده
We study fragmentation of a random recursive tree into a forest by repeated removal of nodes. The initial tree consists of N nodes and it is generated by sequential addition of nodes with each new node attaching to a randomly-selected existing node. As nodes are removed from the tree, one at a time, the tree dissolves into an ensemble of separate trees, namely, a forest. We study statistical properties of trees and nodes in this heterogeneous forest, and find that the fraction of remaining nodes m characterizes the system in the limit N → ∞. We obtain analytically the size density φs of trees of size s. The size density has power-law tail φs ∼ s −α with exponent α = 1 + 1 m . Therefore, the tail becomes steeper as further nodes are removed, and the fragmentation process is unusual in that exponent α increases continuously with time. We also extend our analysis to the case where nodes are added as well as removed, and obtain the asymptotic size density for growing trees.
منابع مشابه
Cutting down $\mathbf p$-trees and inhomogeneous continuum random trees
We study a fragmentation of the p-trees of Camarri and Pitman [Elect. J. Probab., vol. 5, pp. 1–18, 2000]. We give exact correspondences between the p-trees and trees which encode the fragmentation. We then use these results to study the fragmentation of the ICRTs (scaling limits of p-trees) and give distributional correspondences between the ICRT and the tree encoding the fragmentation. The th...
متن کاملConsistent Markov branching trees with discrete edge lengths∗
We study consistent collections of random fragmentation trees with random integervalued edge lengths. We prove several equivalent necessary and sufficient conditions under which Geometrically distributed edge lengths can be consistently assigned to a Markov branching tree. Among these conditions is a characterization by a unique probability measure, which plays a role similar to the dislocation...
متن کاملThe genealogy of self-similar fragmentations with negative index as a continuum random tree
We encode a certain class of stochastic fragmentation processes, namely self-similar fragmentation processes with a negative index of self-similarity, into a metric family tree which belongs to the family of Continuum Random Trees of Aldous. When the splitting times of the fragmentation are dense near 0, the tree can in turn be encoded into a continuous height function, just as the Brownian Con...
متن کاملRandom Ordinality Ensembles A Novel Ensemble Method for Multi-valued Categorical Data
Data with multi-valued categorical attributes can cause major problems for decision trees. The high branching factor can lead to data fragmentation, where decisions have little or no statistical support. In this paper, we propose a new ensemble method, Random Ordinality Ensembles (ROE), that circumvents this problem, and provides significantly improved accuracies over other popular ensemble met...
متن کاملContinuum Tree Asymptotics of Discrete Fragmentations and Applications to Phylogenetic Models by Bénédicte Haas, Grégory Miermont, Jim Pitman
Given any regularly varying dislocation measure, we identify a natural self-similar fragmentation tree as scaling limit of discrete fragmentation trees with unit edge lengths. As an application, we obtain continuum random tree limits of Aldous’s beta-splitting models and Ford’s alpha models for phylogenetic trees. This confirms in a strong way that the whole trees grow at the same speed as the ...
متن کاملContinuum Tree Asymptotics of Discrete Fragmentations and Applications to Phylogenetic Models
Given any regularly varying dislocation measure, we identify a natural self-similar fragmentation tree as scaling limit of discrete fragmentation trees with unit edge lengths. As an application, we obtain continuum random tree limits of Aldous’s beta-splitting models and Ford’s alpha models for phylogenetic trees. This confirms in a strong way that the whole trees grow at the same speed as the ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014