3 citations · 5 across the 4 of their papers we have counts for
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stat.ME2024
Estimation and Inference for Change Points in Functional Regression Time Series
Shivam Kumar, Haotian Xu, Haeran Cho +1
In this paper, we study the estimation and inference of change points under a functional linear regression model with changes in the slope function. We present a novel Functional R…
stat.ME2024★ 3 cited
Detection and inference of changes in high-dimensional linear regression with non-sparse structures
Haeran Cho, Tobias Kley, Housen Li
For data segmentation in high-dimensional linear regression settings, the regression parameters are often assumed to be sparse segment-wise, which enables many existing methods to…
stat.ME2022★ 2 cited
High-dimensional data segmentation in regression settings permitting temporal dependence and non-Gaussianity
Haeran Cho, Dom Owens
We propose a data segmentation methodology for the high-dimensional linear regression problem where regression parameters are allowed to undergo multiple changes. The proposed meth…