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Recursive parameter estimation: asymptotic expansion

机译:递归参数估计:渐近展开

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摘要

This paper is concerned with the asymptotic behaviour of estimation procedures which are recursive in the sense that each successive estimator is obtained from the previous one by a simple adjustment. The results of the paper can be used to determine the form of the recursive procedure which is expected to have the same asymptotic properties as the corresponding non-recursive one defined as a solution of the corresponding estimating equation. Several examples are given to illustrate the theory, including an application to estimation of parameters in exponential families of Markov processes.
机译:本文关注的是递归估计程序的渐近行为,即每个连续的估计量都是通过简单调整从前一个估计量中获得的,这是递归的。本文的结果可用于确定递归程序的形式,该形式应具有与定义为相应估计方程解的相应非递归函数相同的渐近性质。给出了几个示例来说明该理论,包括将其应用于估计马尔可夫过程指数族中的参数。

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