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arXiv 2001.08492math.PR
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具有平稳数的随机变量的特征

Characterization of random variables with stationary digits

Horia Cornean, Ira W. Herbst, Jesper Møller, Benjamin Støttrup, Kasper S. Sørensen

摘要:

设$q\ge2$为整数,$\{X_n\}_{n\geq 1}$为状态空间为$\{0,\ldots,q-1\}$的随机过程,$F$为$\sum_{n=1}^\infty X_n q^{-n}$的累积分布函数.我们表明,平稳性的$\{X_n\}_{n\geq 1}$是等价的一个功能方程遵守$F$,并使用此来表征的特征功能的$X$和结构的$F$在其Lebesgue分解。更准确地说,虽然$F$的绝对连续分量只能是单位区间上的均匀分布,但其离散分量只能是有限支持度概率分布的某些显式可计算CDF的可数凸组合。证明了$\mathrm{d} F$是Rajchman测度当且仅当$F $是$[0,1]$上的一致CDF.

英文摘要:

Let $q\ge2$ be an integer, $\{X_n\}_{n\geq 1}$ a stochastic process with state space $\{0,\ldots,q-1\}$, and $F$ the cumulative distribution function (CDF) of $\sum_{n=1}^\infty X_n q^{-n}$. We show that stationarity of $\{X_n\}_{n\geq 1}$ is equivalent to a functional equation obeyed by $F$ and use this to characterize the characteristic function of $X$ and the structure of $F$ in terms of its Lebesgue decomposition. More precisely, while the absolutely continuous component of $F$ can only be the uniform distribution on the unit interval, its discrete component can only be a countable convex combination of certain explicitly computable CDFs for probability distributions with finite support. We also show that $\mathrm{d} F$ is a Rajchman measure if and only if $F $ is the uniform CDF on $[0,1]$.

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