摘要翻译：
提出了一种离散时间随机过程的估计方法，这些随机过程具有难以处理的似然函数，但可以方便地用积分变换来表示，如特征函数、Laplace变换或概率母函数。该方法包括构造符合拟似然一般框架的基于变换的鞅估计函数类。在离散时间随机过程的参数设定下，通过将不可用得分函数投影到由这些类构成的特殊线性空间上，得到变换拟得分函数。通过任一主要积分变换对过程的描述，通过最优组合变换鞅拟得分函数，使得在无限维Hilbert空间中对得分函数的任意逼近成为可能。它还允许将拟似然方法的应用范围扩展到具有无穷大条件二阶矩的过程。
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英文标题：
《Transform martingale estimating functions》
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作者：
T. Merkouris
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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：
  An estimation method is proposed for a wide variety of discrete time stochastic processes that have an intractable likelihood function but are otherwise conveniently specified by an integral transform such as the characteristic function, the Laplace transform or the probability generating function. This method involves the construction of classes of transform-based martingale estimating functions that fit into the general framework of quasi-likelihood. In the parametric setting of a discrete time stochastic process, we obtain transform quasi-score functions by projecting the unavailable score function onto the special linear spaces formed by these classes. The specification of the process by any of the main integral transforms makes possible an arbitrarily close approximation of the score function in an infinite-dimensional Hilbert space by optimally combining transform martingale quasi-score functions. It also allows an extension of the domain of application of quasi-likelihood methodology to processes with infinite conditional second moment.
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PDF链接：
https://arxiv.org/pdf/711.3577