The height of record‐biased trees

Pub Date : 2021-12-10 DOI:10.1002/rsa.21110
Benoît Corsini
{"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":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1002/rsa.21110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
记录偏向树的高度
给定一个排列σ $$ \sigma $$,将值σ(1),…,σ(n) $$ \sigma (1),\dots, \sigma (n) $$递归插入到二叉树中,使每个节点的标签大于其左子树的标签,小于其右子树的标签,得到其对应的二叉搜索树。在本文中,我们研究从排列的记录偏置模型中绘制的二叉搜索树的高度,该模型在排列集合上的概率度量与θrecord(σ) $$ {\theta}^{\mathrm{record}\left(\sigma \right)} $$成正比,其中record(σ)=|{i∈[n]:∀jσ(j)}| $$ \mathrm{record}\left(\sigma \right)=\mid \left\{i\in \left[n\right]:\forall j\sigma (j)\right\}\mid $$。我们证明了由大小为n $$ n $$且参数为θ $$ \theta $$的记录偏置排列建立的二叉搜索树的高度为(1+o (1)){maxc∗logn,θlog(1+n/θ)}$$ \left(1+{o}_{\mathbb{P}}(1)\right)\max \left\{{c}^{\ast}\log n,\kern0.3em \theta \log \left(1+n/\theta \right)\right\} $$阶,从而扩展了Devroye关于高度或随机二叉搜索树的先前结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1