1 citations · 1 across the 5 of their papers we have counts for
5 papers
On a fast consistent selection of nested models with possibly unnormalized probability densities
Rong Bian, Kung-Sik Chan, Bing Cheng +1
Models with unnormalized probability density functions are ubiquitous in statistics, artificial intelligence and many other fields. However, they face significant challenges in mod…
Adaptive Change Point Detection with Matrix Time Series: Leveraging Structured Mean Shifts
Xinyu Zhang, Kung-Sik Chan
In high-dimensional time series, the component processes are often assembled into a matrix to display their interrelationship. We focus on detecting mean shifts with unknown change…
Mixture Matrix-valued Autoregressive Model
Fei Wu, Kung-Sik Chan
Time series of matrix-valued data are increasingly available in various areas including economics, finance, social science, among others. These data may shed light on the inter-dyn…
Spectral Change Point Estimation for High Dimensional Time Series by Sparse Tensor Decomposition
Xinyu Zhang, Kung-Sik Chan
Multivariate time series may be subject to partial structural changes over certain frequency band, for instance, in neuroscience. We study the change point detection problem with h…
Testing for threshold regulation in presence of measurement error with an application to the PPP hypothesis
Kung-Sik Chan, Simone Giannerini, Greta Goracci +1
Regulation is an important feature characterising many dynamical phenomena and can be tested within the threshold autoregressive setting, with the null hypothesis being a global no…