4 citations · 5 across the 3 of their papers we have counts for
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stat.ME2021
Sparse logistic functional principal component analysis for binary data
Rou Zhong, Shishi Liu, Haocheng Li +1
Functional binary datasets occur frequently in real practice, whereas discrete characteristics of the data can bring challenges to model estimation. In this paper, we propose a spa…
stat.ME2021★ 1 cited
Functional principal component analysis estimator for non-Gaussian data
Rou Zhong, Shishi Liu, Haocheng Li +1
Functional principal component analysis (FPCA) could become invalid when data involve non-Gaussian features. Therefore, we aim to develop a general FPCA method to adapt to such non…
stat.ME2021★ 4 cited
Robust Functional Principal Component Analysis for Non-Gaussian Longitudinal Data
Rou Zhong, Shishi Liu, Jingxiao Zhang +1
Functional principal component analysis is essential in functional data analysis, but the inferences will become unconvincing when some non-Gaussian characteristics occur, such as…