摘要翻译：
我们考虑的估计过程是递归的，因为每一个连续的估计量都是由前一个估计量通过简单的调整得到的。本文所考虑的模型是非常一般的，因为我们没有对观测过程的概率性质施加任何初步限制，并且涵盖了广泛的一类非线性递归过程。本文研究了递推估计的渐近性态。本文的结果可以用来确定一个递推过程的形式，该递推过程与定义为相应估计方程的解的相应非递推过程具有相同的渐近性质。
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英文标题：
《Recursive Parameter Estimation: Asymptotic expansion》
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作者：
Teo Sharia
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最新提交年份：
2007
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分类信息：

一级分类：Mathematics        数学
二级分类：Statistics Theory        统计理论
分类描述：Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计：例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
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一级分类：Statistics        统计学
二级分类：Statistics Theory        统计理论
分类描述：stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近，贝叶斯推论，决策理论，估计，基础，推论，检验。
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英文摘要：
  We consider estimation procedures which are recursive in the sense that each successive estimator is obtained from the previous one by a simple adjustment. The model considered in the paper is very general as we do not impose any preliminary restrictions on the probabilistic nature of the observation process and cover a wide class of nonlinear recursive procedures. In this paper we study asymptotic behaviour of the recursive estimators. The results of the paper can be used to determine the form of a 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.
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PDF链接：
https://arxiv.org/pdf/705.1783