{"title":"记录偏向树的高度","authors":"Benoît Corsini","doi":"10.1002/rsa.21110","DOIUrl":null,"url":null,"abstract":"Given a permutation σ$$ \\sigma $$ , its corresponding binary search tree is obtained by recursively inserting the values σ(1),…,σ(n)$$ \\sigma (1),\\dots, \\sigma (n) $$ into a binary tree so that the label of each node is larger than the labels of its left subtree and smaller than the labels of its right subtree. In this article, we study the height of binary search trees drawn from the record‐biased model of permutations whose probability measure on the set of permutations is proportional to θrecord(σ)$$ {\\theta}^{\\mathrm{record}\\left(\\sigma \\right)} $$ , where record(σ)=|{i∈[n]:∀jσ(j)}|$$ \\mathrm{record}\\left(\\sigma \\right)=\\mid \\left\\{i\\in \\left[n\\right]:\\forall j\\sigma (j)\\right\\}\\mid $$ . We show that the height of a binary search tree built from a record‐biased permutation of size n$$ n $$ with parameter θ$$ \\theta $$ is of order (1+oℙ(1))max{c∗logn,θlog(1+n/θ)}$$ \\left(1+{o}_{\\mathbb{P}}(1)\\right)\\max \\left\\{{c}^{\\ast}\\log n,\\kern0.3em \\theta \\log \\left(1+n/\\theta \\right)\\right\\} $$ , hence extending previous results of Devroye on the height or random binary search trees.","PeriodicalId":54523,"journal":{"name":"Random Structures & Algorithms","volume":"206 1","pages":"623 - 644"},"PeriodicalIF":0.9000,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The height of record‐biased trees\",\"authors\":\"Benoît Corsini\",\"doi\":\"10.1002/rsa.21110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Given a permutation σ$$ \\\\sigma $$ , its corresponding binary search tree is obtained by recursively inserting the values σ(1),…,σ(n)$$ \\\\sigma (1),\\\\dots, \\\\sigma (n) $$ into a binary tree so that the label of each node is larger than the labels of its left subtree and smaller than the labels of its right subtree. In this article, we study the height of binary search trees drawn from the record‐biased model of permutations whose probability measure on the set of permutations is proportional to θrecord(σ)$$ {\\\\theta}^{\\\\mathrm{record}\\\\left(\\\\sigma \\\\right)} $$ , where record(σ)=|{i∈[n]:∀jσ(j)}|$$ \\\\mathrm{record}\\\\left(\\\\sigma \\\\right)=\\\\mid \\\\left\\\\{i\\\\in \\\\left[n\\\\right]:\\\\forall j\\\\sigma (j)\\\\right\\\\}\\\\mid $$ . We show that the height of a binary search tree built from a record‐biased permutation of size n$$ n $$ with parameter θ$$ \\\\theta $$ is of order (1+oℙ(1))max{c∗logn,θlog(1+n/θ)}$$ \\\\left(1+{o}_{\\\\mathbb{P}}(1)\\\\right)\\\\max \\\\left\\\\{{c}^{\\\\ast}\\\\log n,\\\\kern0.3em \\\\theta \\\\log \\\\left(1+n/\\\\theta \\\\right)\\\\right\\\\} $$ , hence extending previous results of Devroye on the height or random binary search trees.\",\"PeriodicalId\":54523,\"journal\":{\"name\":\"Random Structures & Algorithms\",\"volume\":\"206 1\",\"pages\":\"623 - 644\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2021-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Random Structures & Algorithms\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1002/rsa.21110\",\"RegionNum\":3,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Random Structures & Algorithms","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1002/rsa.21110","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
Given a permutation σ$$ \sigma $$ , its corresponding binary search tree is obtained by recursively inserting the values σ(1),…,σ(n)$$ \sigma (1),\dots, \sigma (n) $$ into a binary tree so that the label of each node is larger than the labels of its left subtree and smaller than the labels of its right subtree. In this article, we study the height of binary search trees drawn from the record‐biased model of permutations whose probability measure on the set of permutations is proportional to θrecord(σ)$$ {\theta}^{\mathrm{record}\left(\sigma \right)} $$ , where record(σ)=|{i∈[n]:∀jσ(j)}|$$ \mathrm{record}\left(\sigma \right)=\mid \left\{i\in \left[n\right]:\forall j\sigma (j)\right\}\mid $$ . We show that the height of a binary search tree built from a record‐biased permutation of size n$$ n $$ with parameter θ$$ \theta $$ is of order (1+oℙ(1))max{c∗logn,θlog(1+n/θ)}$$ \left(1+{o}_{\mathbb{P}}(1)\right)\max \left\{{c}^{\ast}\log n,\kern0.3em \theta \log \left(1+n/\theta \right)\right\} $$ , hence extending previous results of Devroye on the height or random binary search trees.
期刊介绍:
It is the aim of this journal to meet two main objectives: to cover the latest research on discrete random structures, and to present applications of such research to problems in combinatorics and computer science. The goal is to provide a natural home for a significant body of current research, and a useful forum for ideas on future studies in randomness.
Results concerning random graphs, hypergraphs, matroids, trees, mappings, permutations, matrices, sets and orders, as well as stochastic graph processes and networks are presented with particular emphasis on the use of probabilistic methods in combinatorics as developed by Paul Erdõs. The journal focuses on probabilistic algorithms, average case analysis of deterministic algorithms, and applications of probabilistic methods to cryptography, data structures, searching and sorting. The journal also devotes space to such areas of probability theory as percolation, random walks and combinatorial aspects of probability.