We investigate the large-sample behavior of change-point tests based on weighted two-sample U-statistics, in case short-range dependent data. Under some mild mixing conditions, we establish convergence test statistic to an extreme value distribution. A simulation study shows that are superior non-weighted versions when occurs near boundary time interval, while they loose power center.

Abstract Creating 3D models of the static environment is an important task for advancement driver assistance systems and autonomous driving. In this work, a reference map created from Mobile Mapping “light detection ranging” (LiDAR) dataset. The data was obtained in 14 measurement runs March to October 2017 Hannover consists total about 15 billion points. point cloud are first segmented by regi...

Abstract Bayesian change-point detection, with latent variable models, allows to perform segmentation of high-dimensional time-series heterogeneous statistical nature. We assume that change-points lie on a lower-dimensional manifold where we aim infer discrete representation via subsets variables. For this particular model, full inference is computationally unfeasible and pseudo-observations ba...