{"title":"How Many Digits are Needed?","authors":"Ira W. Herbst, Jesper Møller, Anne Marie Svane","doi":"10.1007/s11009-024-10073-2","DOIUrl":null,"url":null,"abstract":"<p>Let <span>\\(X_1,X_2,...\\)</span> be the digits in the base-<i>q</i> expansion of a random variable <i>X</i> defined on [0, 1) where <span>\\(q\\ge 2\\)</span> is an integer. For <span>\\(n=1,2,...\\)</span>, we study the probability distribution <span>\\(P_n\\)</span> of the (scaled) remainder <span>\\(T^n(X)=\\sum _{k=n+1}^\\infty X_k q^{n-k}\\)</span>: If <i>X</i> has an absolutely continuous CDF then <span>\\(P_n\\)</span> converges in the total variation metric to the Lebesgue measure <span>\\(\\mu \\)</span> on the unit interval. Under weak smoothness conditions we establish first a coupling between <i>X</i> and a non-negative integer valued random variable <i>N</i> so that <span>\\(T^N(X)\\)</span> follows <span>\\(\\mu \\)</span> and is independent of <span>\\((X_1,...,X_N)\\)</span>, and second exponentially fast convergence of <span>\\(P_n\\)</span> and its PDF <span>\\(f_n\\)</span>. We discuss how many digits are needed and show examples of our results.</p>","PeriodicalId":18442,"journal":{"name":"Methodology and Computing in Applied Probability","volume":"20 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Methodology and Computing in Applied Probability","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s11009-024-10073-2","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
Let \(X_1,X_2,...\) be the digits in the base-q expansion of a random variable X defined on [0, 1) where \(q\ge 2\) is an integer. For \(n=1,2,...\), we study the probability distribution \(P_n\) of the (scaled) remainder \(T^n(X)=\sum _{k=n+1}^\infty X_k q^{n-k}\): If X has an absolutely continuous CDF then \(P_n\) converges in the total variation metric to the Lebesgue measure \(\mu \) on the unit interval. Under weak smoothness conditions we establish first a coupling between X and a non-negative integer valued random variable N so that \(T^N(X)\) follows \(\mu \) and is independent of \((X_1,...,X_N)\), and second exponentially fast convergence of \(P_n\) and its PDF \(f_n\). We discuss how many digits are needed and show examples of our results.
期刊介绍:
Methodology and Computing in Applied Probability will publish high quality research and review articles in the areas of applied probability that emphasize methodology and computing. Of special interest are articles in important areas of applications that include detailed case studies. Applied probability is a broad research area that is of interest to many scientists in diverse disciplines including: anthropology, biology, communication theory, economics, epidemiology, finance, linguistics, meteorology, operations research, psychology, quality control, reliability theory, sociology and statistics.
The following alphabetical listing of topics of interest to the journal is not intended to be exclusive but to demonstrate the editorial policy of attracting papers which represent a broad range of interests:
-Algorithms-
Approximations-
Asymptotic Approximations & Expansions-
Combinatorial & Geometric Probability-
Communication Networks-
Extreme Value Theory-
Finance-
Image Analysis-
Inequalities-
Information Theory-
Mathematical Physics-
Molecular Biology-
Monte Carlo Methods-
Order Statistics-
Queuing Theory-
Reliability Theory-
Stochastic Processes