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Rank Determination in Tensor Factor Model

Yuefeng Han, Rong Chen, Cun-Hui Zhang

arXiv 13 Nov 2020 · Statistics — Methodology · publishedElectronic Journal of Statistics (2022) · 32 citations (OpenAlex)

arXiv:2011.07131 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Factor model is an appealing and effective analytic tool for high-dimensional time series, with a wide range of applications in economics, finance and statistics. This paper develops two criteria for the determination of the number of factors for tensor factor models where the signal part of an observed tensor time series assumes a Tucker decomposition with the core tensor as the factor tensor. The task is to determine the dimensions of the core tensor. One of the proposed criteria is similar to information based criteria of model selection, and the other is an extension of the approaches based on the ratios of consecutive eigenvalues often used in factor analysis for panel time series. Theoretically results, including sufficient conditions and convergence rates, are established. The results include the vector factor models as special cases, with an additional convergence rates. Simulation studies provide promising finite sample performance for the two criteria.

Citation extraction

60
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159
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distinct cited
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appendix boundary found by appendix_command · 46% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1barticle[author] Hallin, MarcM. Liska, RomanR (2007) )1.000145100%
2barticle[author] Bai, JushanJ. Ng, SerenaS (2002) )1.000133100%
3barticle[author] Lam, CliffordC. Yao, QiweiQ (2012) )1.000124100%
4barticle[author] Wang, DongD., Liu, XialuX. Chen, RongR (2019) ) self0.9507386%
5barticle[author] Alessi, LuciaL., Barigozzi, MatteoM. Capasso, MarcoM (2010) )0.92843100%
6barticle[author] Han, YuefengY., Chen, RongR., Yang, DanD. Zhang, Cu… (2020) ) self0.89124771%
7barticle[author] Chen, RongR., Yang, DanD. Zhang, Cun-HuiC.-H (2021) ) self0.88119568%
8barticle[author] Amengual, DanteD. Watson, Mark WM. W (2007) )0.84333100%
9barticle[author] Ahn, Seung CS. C. Horenstein, Alex RA. R (2013) )0.73732100%
10barticle[author] Hoff, Peter D.P. D (2011) )0.64422100%

Showing the top 10 of 60 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1CP Factor Model for Dynamic Tensors0.84333
2Simultaneous Decorrelation of Matrix Time Series0.64422
3Dynamic Matrix Factor Models for High Dimensional Time Series0.64422
4Factor Network Autoregressions0.58531
5Estimation and Inference for CP Tensor Factor Models0.51142
6Tensor PCA for Factor Models0.40511
7Econometrics of Machine Learning Methods in Economic Forecasting0.40511
8Reduced-Rank Matrix Autoregressive Models: A Medium $N$ Approach0.40511
9Identification and Estimation for Matrix Time Series CP-factor Models0.40511
10Estimation of large approximate dynamic matrix factor models based on the EM algorithm and Kalman filtering0.40511