Point processes are stochastic models generating interacting points or events in time, space, etc. Among characteristics of these models, first-order intensity and conditional intensity functions are often considered. We focus on inhomogeneous parametric forms of these functions assumed to depend on a certain number of spatial covariates. When this number of covariates is large, we are faced with a high-dimensional problem. This paper provides an overview of these questions and existing solutions based on regularizations.

翻译：点过程是生成时间、空间等维度中相互作用的点或事件的随机模型。在这些模型的特征中，一阶强度函数和条件强度函数常被关注。本文聚焦于这些函数的非齐次参数形式，假定其依赖于一定数量的空间协变量。当协变量数量较大时，我们面临高维问题。本文综述了这些问题及基于正则化的现有解决方案。