Smoothing techniques and estimation methods for nonstationary Boolean models with applications to coverage processes
非平稳布尔模型的平滑估计及覆盖过程应用
Kernel smoothing methods are applied to nonparametric estimation for nonstationary Boolean models. In many applications only exposed tangent points of the models are observable rather than full realisations. Several methods are developed for estimating the distribution of the underlying Boolean model from observation of the exposed tangent points. In particular, estimation methods for coverage processes are studied in detail and applied to neurobiological data.