Characterization and Construction of Singular Distribution Functions for Random Base-q Expansions whose Digits Generate a Stationary Process.

Let $F$ be the cumulative distribution function (CDF) of the base-$q$ expansion $\sum_{n=1}^\infty X_n q^{-n}$, where $q\ge2$ is an integer and $\{X_n\}_{n\geq 1}$ is a stochastic process with state space $\{0,\ldots,q-1\}$. We show that stationarity of $\{X_n\}_{n\geq 1}$ is equivalent to a certain functional equation obeyed by $F$, which enables us to give a complete characterization of the structure of $F$. In particular, we prove that the absolutely continuous component of $F$ can only be the uniform distribution on the unit interval while its discrete component can only be a countable convex combination of certain explicitly computable CDFs for probability distributions with finite support. Moreover, we show that for a large class of stationary stochastic processes, their corresponding $F$ is singular (that is, $F'=0$ almost everywhere) and continuous; and often also strictly increasing on $[0,1]$. We also consider geometric constructions and `relatively closed form expressions' of $F$. Finally, we study special cases of models, including stationary Markov chains of any order, stationary renewal point processes, and mixtures of such models, where expressions and plots of $F$ will be exemplified.