not: Narrowest-Over-Threshold Change-Point Detection
Provides efficient implementation of the Narrowest-Over-Threshold methodology for detecting an unknown number of change-points occurring at unknown locations in one-dimensional data following 'deterministic signal + noise' model. Currently implemented scenarios are: piecewise-constant signal, piecewise-constant signal with a heavy-tailed noise, piecewise-linear signal, piecewise-quadratic signal, piecewise-constant signal and with piecewise-constant variance of the noise. For details, see Baranowski, Chen and Fryzlewicz (2019) <doi:10.1111/rssb.12322>.
||graphics, stats, splines
||Rafal Baranowski, Yining Chen, Piotr Fryzlewicz
||Yining Chen <Y.Chen101 at lse.ac.uk>
Please use the canonical form
to link to this page.