Bitseki and Delmas (2021) have studied recently the central limit theorem for kernel estimator of invariant density in bifurcating Markov chains models. We complete their work by proving a moderate deviation principle for this estimator. Unlike the work of Bitseki and Gorgui (2021), it is interesting to see that the distinction of the two regimes disappears and that we are able to get moderate deviation principle for large values of the ergodic rate. It is also interesting and surprising to see that for moderate deviation principle, the ergodic rate begins to have an impact on the choice of the bandwidth for values smaller than in the context of central limit theorem studied by Bitseki and Delmas (2021).
翻译:Bitseki 和 Delmas (2021年)最近研究了马可夫链条模型中不变化密度内核测算器的核心限值。 我们通过证明该测算器的适度偏差原则完成了它们的工作。 与Bitseki 和 Gorgui (2021年)的工作不同,令人感兴趣的是,这两个制度的区别已经消失,而且我们能够为大额ergodic 率获得中度偏差原则。 同样令人感兴趣的是,从中度偏差原则来看,ergodic 率开始影响比Bitseki 和 Delmas (2021年) 所研究的中度限值范围小值的带宽选择。