Characterization of random variables with stationary digits

Abstract

Let q2 be an integer, \Xn\n≥ 1 a stochastic process with state space \0,…,q-1\, and F the cumulative distribution function (CDF) of Σn=1∞ Xn q-n. We show that stationarity of \Xn\n≥ 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 d F is a Rajchman measure if and only if F is the uniform CDF on [0,1].

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