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Dimensionality determination: A thresholding double ridge ratio approach

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  • Zhu, Xuehu
  • Guo, Xu
  • Wang, Tao
  • Zhu, Lixing

Abstract

Underdetermination of model dimensionality (order) is a longstanding problem when existing eigendecomposition-based criteria are used. To alleviate this difficulty, we propose a thresholding double ridge ratio criterion in this paper. Unlike all existing eigendecomposition-based criteria, the proposed criterion can provide a consistent estimate even when there are several local minima. For illustration, we present the generic strategy with three important applications: dimension reduction in regressions with fixed and divergent dimensions; model checking with local alternative models; and ultra-high dimensional approximate factor models. Numerical studies are conducted to examine the finite sample performance of the proposed method and a real data example is analyzed for illustration.

Suggested Citation

  • Zhu, Xuehu & Guo, Xu & Wang, Tao & Zhu, Lixing, 2020. "Dimensionality determination: A thresholding double ridge ratio approach," Computational Statistics & Data Analysis, Elsevier, vol. 146(C).
    • Handle: RePEc:eee:csdana:v:146:y:2020:i:c:s0167947320300013
    DOI: 10.1016/j.csda.2020.106910
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    References listed on IDEAS

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    Cited by:

    1. Jiasen Zheng & Lixing Zhu, 2021. "Determining the number of canonical correlation pairs for high-dimensional vectors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 737-756, August.
    2. Zeng, Yicheng & Zhu, Lixing, 2023. "Order determination for spiked-type models with a divergent number of spikes," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    3. Junmin Liu & Deli Zhu & Luoyao Yu & Xuehu Zhu, 2023. "Specification testing of partially linear single-index models: a groupwise dimension reduction-based adaptive-to-model approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(1), pages 232-262, March.
    4. Xuehu Zhu & Jun Lu & Jun Zhang & Lixing Zhu, 2021. "Testing for conditional independence: A groupwise dimension reduction‐based adaptive‐to‐model approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 549-576, June.

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