### Abstract

Under a notion of "splitting" the existence of a unique invariant probability, and a geometric rate of convergence to it in an appropriate metric, are established for Markov processes on a general state space S generated by iterations of i.i.d. maps on S. As corollaries we derive extensions of earlier results of Dubins and Freedman;^{(17)} Yahav;^{(30)} and Bhattacharya and Lee^{(6)} for monotone maps. The general theorem applies in other contexts as well. It is also shown that the Dubins-Freedman result on the "necessity" of splitting in the case of increasing maps does not hold for decreasing maps, although the sufficiency part holds for both. In addition, the asymptotic stationarity of the process generated by i.i.d. nondecreasing maps is established without the requirement of continuity. Finally, the theory is applied to the random iteration of two (nonmonotone) quadratic maps each with two repelling fixed points and an attractive period-two orbit.

Original language | English (US) |
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Pages (from-to) | 1067-1087 |

Number of pages | 21 |

Journal | Journal of Theoretical Probability |

Volume | 12 |

Issue number | 4 |

DOIs | |

State | Published - Jan 1 1999 |

### Keywords

- Asymptotic stationarity
- Iteration of i.i.d. maps
- Markov processes
- Monotone maps
- Quadratic maps

### ASJC Scopus subject areas

- Statistics and Probability
- Mathematics(all)
- Statistics, Probability and Uncertainty

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## Cite this

*Journal of Theoretical Probability*,

*12*(4), 1067-1087. https://doi.org/10.1023/A:1021601421920