论文标题
COX流程是由线性网络上转换的高斯流程驱动的 - 审查和新贡献
Cox processes driven by transformed Gaussian processes on linear networks -- A review and new contributions
论文作者
论文摘要
线性网络上缺乏点过程模型。对于任意线性网络，我们通过转换用于驱动Cox过程的随机强度函数的各向同性高斯过程，以各种方式考虑具有各种方式获得的COX过程的新模型。特别是，我们介绍了线性网络上的Log Gaussian，中断和永久性COX流程给出的三个模型类，并首次考虑此类模型参数家族的统计过程和应用。此外，我们为线性网络上的高斯过程构建了新的仿真算法，并讨论是否应将地球标准或电阻度量用于本文研究的COX过程。
There is a lack of point process models on linear networks. For an arbitrary linear network, we consider new models for a Cox process with an isotropic pair correlation function obtained in various ways by transforming an isotropic Gaussian process which is used for driving the random intensity function of the Cox process. In particular we introduce three model classes given by log Gaussian, interrupted, and permanental Cox processes on linear networks, and consider for the first time statistical procedures and applications for parametric families of such models. Moreover, we construct new simulation algorithms for Gaussian processes on linear networks and discuss whether the geodesic metric or the resistance metric should be used for the kind of Cox processes studied in this paper.
