How Many Digits are Needed?

IF 1 4区 数学 Q3 STATISTICS & PROBABILITY
Ira W. Herbst, Jesper Møller, Anne Marie Svane
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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.

Abstract Image

需要多少位数?
让\(X_1,X_2,...\)是定义在[0, 1]上的随机变量X的基q展开中的数字,其中\(q\ge 2\) 是整数。对于 n=1,2,...\),我们研究(缩放)余数 \(T^n(X)=sum _{k=n+1}^\infty X_k q^{n-k}\) 的概率分布 \(P_n\):如果 X 有一个绝对连续的 CDF,那么 \(P_n\) 在总变化度量中收敛于单位区间上的 Lebesgue 度量 \(\mu\) 。在弱平稳条件下,我们首先建立了X和一个非负整数值随机变量N之间的耦合,这样\(T^N(X)\)就跟随\(\mu \)并且与\((X_1,...,X_N)\)无关,其次\(P_n\)和它的PDF\(f_n\)呈指数级快速收敛。我们将讨论需要多少位数,并举例说明我们的结果。
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来源期刊
CiteScore
1.70
自引率
0.00%
发文量
58
审稿时长
6-12 weeks
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
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