空间点过程强度估计的凸与非凸正则化方法
Convex and non-convex regularization methods for spatial point processes intensity estimation
摘要：
本文讨论了空间点过程强度估计的特征选择过程。我们考虑正则化版本的估计方程的基础上坎贝尔定理来自两个经典的功能：泊松似然和逻辑斯谛回归似然。我们提供了一般条件的空间点过程和罚函数，确保一致性，稀疏性和渐近正态性。我们讨论的数值实现和评估有限样本的模拟研究。最后，热带林业数据集的应用程序说明了所提出的方法的使用。
英文摘要：
This paper deals with feature selection procedures for spatial point processes intensity estimation. We consider regularized versions of estimating equations based on Campbell theorem derived from two classical functions: Poisson likelihood and logistic regression likelihood. We provide general conditions on the spatial point processes and on penalty functions which ensure consistency, sparsity and asymptotic normality. We discuss the numerical implementation and assess finite sample properties in a simulation study. Finally, an application to tropical forestry datasets illustrates the use of the proposed methods.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
