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04/03/2022
Robust PCA for High Dimensional Data based on Characteristic Transformation
In this paper, we propose a novel robust Principal Component Analysis (P...
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03/13/2022
Homogeneity and Sub-homogeneity Pursuit: Iterative Complement Clustering PCA
Principal component analysis (PCA), the most popular dimension-reduction...
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03/09/2022
Factor-augmented model for functional data
We propose modeling raw functional data as a mixture of a smooth functio...
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01/10/2022
Spiked eigenvalues of high-dimensional sample autocovariance matrices: CLT and applications
High-dimensional autocovariance matrices play an important role in dimen...
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01/04/2022
Clustering and Forecasting Multiple Functional Time Series
Modelling and forecasting homogeneous age-specific mortality rates of mu...
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12/01/2021
AR-sieve Bootstrap for High-dimensional Time Series
This paper proposes a new AR-sieve bootstrap approach on high-dimensiona...
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09/09/2021
Multi-population mortality forecasting using high-dimensional functional factor models
This paper proposes a two-fold factor model for high-dimensional functio...
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06/02/2021
Feature Extraction for Functional Time Series: Theory and Application to NIR Spectroscopy Data
We propose a novel method to extract global and local features of functi...
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02/08/2021
Data-adaptive Dimension Reduction for US Mortality Forecasting
Forecasting accuracy of mortality data is important for the management o...
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02/04/2021
Factor-augmented Smoothing Model for Functional Data
We propose modeling raw functional data as a mixture of a smooth functio...
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02/03/2021
Mortality Forecasting using Factor Models: Time-varying or Time-invariant Factor Loadings?
Many existing mortality models follow the framework of classical factor ...
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04/15/2019
Estimation of Cross-Sectional Dependence in Large Panels
Accurate estimation for extent of crosssectional dependence in large pan...
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10/02/2018