The relations of the newer multivariate statistical methods to factor analysis.

By H. Hotelling. 1957

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1. Lingzhou Xue
2. Jianqing Fan
3. Jiawei Yao
4. Xiangrong Yin
5. Hansheng Wang
6. Clifford Lam
7. Peng Zeng
8. Yu Zhu

Citations in the corpus

• Sufficient Forecasting Using Factor Models (2015, methodology): “Motivated by the classic principal component regression (Kendall, 1957; Hotelling, 1957), Stock and Watson (2002 a , b ) employed a similar idea to forecast a single time series from a large number of predictors: first use the principal component analysis (PCA) to estimate the underlying common…”
• Fourier Methods for Estimating the Central Subspace and the Central Mean Subspace in Regression (2006, methodology): “To mitigate the curse of dimensionality, various dimension reduction techniques have been proposed in the literature, including projection pursuit regression (Friedman and Stuetzle 1981) and principal component regression (Hotelling 1957; Kendall 1957).”
• Fisher Lecture: Dimension Reduction in Regression (2007, methodology): “A similar sentiment was expressed by Hotelling (1957), Hawkins and Fatti (1984) and others.”