应用于非正则连分数算法的几乎确定极限定理

IF 1.1 2区 数学 Q3 STATISTICS & PROBABILITY
Claudio Bonanno , Tanja I. Schindler
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引用次数: 0

摘要

考虑测度空间(X,B,μ)上具有μ a σ-有限测度且μ(X)=∞的保守遍历保测度变换T。给定一个可观测的g:X→R,从Aaronson(1997)的结果中我们知道,一般来说,Birkhoff和SNg(X):=∑j=1N(g°Tj−1)(X)的渐近性质强烈依赖于点X∈X,并且对于μ-几乎每个X∈X,不存在SNg(X)/dN→1的序列(dN)。本文考虑g⁄∈L1(X,μ)的情况,并继续在Bonanno和Schindler(2022)中开始的研究。我们证明了对于有限测度集上的诱导映射具有强混合假设的变换T,可以用两种方法获得无界可观测g的SNg(x)的几乎肯定的渐近行为,除了依赖于x的若干求和的SNg和切边。所得的和然后渐近于n的标量倍。结果被应用到一对非正则的连分数算法,向后(或rsamunyi型)的连分数和偶数整数的连分数算法,以获得算法的数字的和的几乎肯定的渐近行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Almost sure limit theorems with applications to non-regular continued fraction algorithms
We consider a conservative ergodic measure-preserving transformation T of the measure space (X,B,μ) with μ a σ-finite measure and μ(X)=. Given an observable g:XR, it is well known from results by Aaronson, see Aaronson (1997), that in general the asymptotic behaviour of the Birkhoff sums SNg(x):=j=1N(gTj1)(x) strongly depends on the point xX, and that there exists no sequence (dN) for which SNg(x)/dN1 for μ-almost every xX. In this paper we consider the case gL1(X,μ) and continue the investigation initiated in Bonanno and Schindler (2022). We show that for transformations T with strong mixing assumptions for the induced map on a finite measure set, the almost sure asymptotic behaviour of SNg(x) for an unbounded observable g may be obtained using two methods, addition to SNg of a number of summands depending on x and trimming. The obtained sums are then asymptotic to a scalar multiple of N. The results are applied to a couple of non-regular continued fraction algorithms, the backward (or Rényi type) continued fraction and the even-integer continued fraction algorithms, to obtain the almost sure asymptotic behaviour of the sums of the digits of the algorithms.
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来源期刊
Stochastic Processes and their Applications
Stochastic Processes and their Applications 数学-统计学与概率论
CiteScore
2.90
自引率
7.10%
发文量
180
审稿时长
23.6 weeks
期刊介绍: Stochastic Processes and their Applications publishes papers on the theory and applications of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests. Characterization, structural properties, inference and control of stochastic processes are covered. The journal is exacting and scholarly in its standards. Every effort is made to promote innovation, vitality, and communication between disciplines. All papers are refereed.
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