4 papers · 1 filter
Nonparametric data segmentation in multivariate time series via joint characteristic functions
Euan T. McGonigle, Haeran Cho
Modern time series data often exhibit complex dependence and structural changes which are not easily characterised by shifts in the mean or model parameters. We propose a nonparame…
Data segmentation algorithms: Univariate mean change and beyond
Haeran Cho, Claudia Kirch
Data segmentation a.k.a. multiple change point analysis has received considerable attention due to its importance in time series analysis and signal processing, with applications i…
Discussion of 'Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection'
Haeran Cho, Claudia Kirch
We discuss the theoretical guarantee provided by the WBS2.SDLL proposed in Fryzlewicz (2020) and explore an alternative, MOSUM-based candidate generation method for the SDLL.
Consistent estimation of high-dimensional factor models when the factor number is over-estimated
Matteo Barigozzi, Haeran Cho
A high-dimensional -factor model for an -dimensional vector time series is characterised by the presence of a large eigengap (increasing with ) between the -th and the…