论文标题
用于逻辑回归估计器的无置渐近学估算值
Infill asymptotics for logistic regression estimators for spatio-temporal point processes
论文作者
论文摘要
本文讨论了对逻辑回归估计量的无置渐近物质，其强度函数的时空点过程是对数线性形式的。我们为Poisson点过程模型的参数建立了强大的一致性和渐近正态性，并演示了如何将这些结果扩展到一般点过程模型。此外，在适当的条件下，我们还将我们的中心限制定理扩展到基于坎贝尔定理的其他无偏估计方程。
This paper discusses infill asymptotics for logistic regression estimators for spatio-temporal point processes whose intensity functions are of log-linear form. We establish strong consistency and asymptotic normality for the parameters of a Poisson point process model and demonstrate how these results can be extended to general point process models. Additionally, under proper conditions, we also extend our central limit theorem to other unbiased estimating equations that are based on the Campbell--Mecke theorem.
