Abstract:
Consider the set of functions $f_{\theta}(x)=|\theta -x|$ on $\mathbf R$. Define a Markov process that starts with a point $x_0 \in \mathbf R$ and continues with $x_{k+1}=f_{\theta_{k+1}}(x_{k})$ with each $\theta _{k+1}$ chosen from a fixed bounded distribution $\mu$ on ${\mathbf R}^+$. We prove the conjecture of Letac that if $\mu$ is not supported on a lattice, then this process has a unique stationary distribution $\pi_{\mu}$ and any distribution converges under iteration to $\pi_{\mu}$ (in the weak-$^*$ topology). We also give a bound on the rate of convergence in the special case that $\mu$ is supported on a two-point set. We hope that the techniques will be useful for the study of other Markov processes where the transition functions have Lipschitz number one.
Keywords:iterated random function, Markov process, stationary distribution.
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