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On estimation of the noise variance in high dimensional probabilistic principal component analysis. (2017). Passemier, Damien ; Yao, Jianfeng ; Li, Zhaoyuan.
In: Journal of the Royal Statistical Society Series B.
RePEc:bla:jorssb:v:79:y:2017:i:1:p:51-67.

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  1. Order determination for spiked-type models with a divergent number of spikes. (2023). Zhu, Lixing ; Zeng, Yicheng.
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:182:y:2023:i:c:s0167947323000154.

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  2. Applications on linear spectral statistics of high-dimensional sample covariance matrix with divergent spectrum. (2023). Liu, Xiaowei ; Zhou, Yirui ; Zhang, Yangchun.
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:178:y:2023:i:c:s0167947322001979.

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  3. A high-dimensional test on linear hypothesis of means under a low-dimensional factor model. (2022). He, Yuanjing ; Cao, Mingxiang.
    In: Metrika: International Journal for Theoretical and Applied Statistics.
    RePEc:spr:metrik:v:85:y:2022:i:5:d:10.1007_s00184-021-00841-2.

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  4. Hypothesis Tests for Principal Component Analysis When Variables are Standardized. (2019). Piepho, Hans-Peter ; Josse, Julie ; Forkman, Johannes.
    In: Journal of Agricultural, Biological and Environmental Statistics.
    RePEc:spr:jagbes:v:24:y:2019:i:2:d:10.1007_s13253-019-00355-5.

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  5. High-Dimensional MVDR Beamforming: Optimized Solutions Based on Spiked Random Matrix Models. (2018). Couillet, Romain ; McKay, Matthew ; Yang, Liusha .
    In: Post-Print.
    RePEc:hal:journl:hal-01957672.

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  6. A supplement on CLT for LSS under a large dimensional generalized spiked covariance model. (2018). Chen, Jiaqi ; Tian, Boping ; Li, Weiming ; Zhang, Yangchun.
    In: Statistics & Probability Letters.
    RePEc:eee:stapro:v:138:y:2018:i:c:p:57-65.

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  7. On two-sample mean tests under spiked covariances. (2018). Wang, Rui ; Xu, Xingzhong.
    In: Journal of Multivariate Analysis.
    RePEc:eee:jmvana:v:167:y:2018:i:c:p:225-249.

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References

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