Tag: Principal Component Analysis
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Robust Forecasting by Functional Principal Component Analysis
This post is based on Hyndman, R. J., & Shahid Ullah, Md. (2007). Robust forecasting of mortality and fertility rates: A functional data approach. Computational Statistics & Data Analysis, 51(10), 4942–4956.
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Survey on Functional Principal Component Analysis
This post is based on Shang, H. L. (2014). A survey of functional principal component analysis. AStA Advances in Statistical Analysis, 98(2), 121–142.
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Common Functional Principal Components
This post is based on Benko, M., Härdle, W., & Kneip, A. (2009). Common functional principal components. The Annals of Statistics, 37(1), 1–34.
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Common Principal Components
This post is based on Flury (1984).
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Generalized Matrix Decomposition
This post is based on the talk given by Dr. Yue Wang at the Department of Statistics and Data Science, Southern University of Science and Technology on Jan. 04, 2020.
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Gradient-based Sparse Principal Component Analysis
This post is based on the talk, Gradient-based Sparse Principal Component Analysis, given by Dr. Yixuan Qiu at the Department of Statistics and Data Science, Southern University of Science and Technology on Jan. 05, 2020.
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Functional PCA
This post is based on Ramsay, J. O., & Silverman, B. W. (2005). Functional data analysis (Second edition). New York, NY: Springer.
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Tensor Completion
Prof. YUAN Ming will give a distinguish lecture on Low Rank Tensor Methods in High Dimensional Data Analysis. To get familiar with his work on tensor, I read his paper, Yuan, M., & Zhang, C.-H. (2016). On Tensor Completion via Nuclear Norm Minimization. Foundations of Computational Mathematics, 16(4), 1031–1068., which is the topic of this post.
- SIR and Its Implementation