Tensor Stein-rules in a generalized tensor regression model
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Publication:6051066
DOI10.1016/j.jmva.2023.105206OpenAlexW4381331525MaRDI QIDQ6051066
Mai Ghannam, Sévérien Nkurunziza
Publication date: 19 September 2023
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmva.2023.105206
asymptotic propertyJames-Stein estimatorsrandom arraytensor shrinkage estimatorsgeneralized tensor regressionmulti-mode covariates
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Parametric inference under constraints (62F30) Multivariate analysis (62Hxx)
Cites Work
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- Tensor-on-Tensor Regression
- Tensor Decompositions and Applications
- Multilinear tensor regression for longitudinal relational data
- On some shrinkage estimators of multivariate location
- Minimax estimation of location vectors for a wide class of densities
- On the invariance principle for nonstationary mixingales
- Minimax estimation of location parameters for spherically symmetric unimodal distributions under quadratic loss
- Shrinkage estimators of the location parameter for certain spherically symmetric distributions
- Proper Bayes minimax estimators of the multivariate normal mean vector for the case of common unknown variances
- Shrinkage estimation
- On improved shrinkage estimators for concave loss
- Sequences of elliptical distributions and mixtures of normal distributions
- The risk of pretest and shrinkage estimators
- Tensor Regression with Applications in Neuroimaging Data Analysis
- Robustness of the likelihood ratio test for detection and estimation of a mean change point in a sequence of elliptically contoured observations
- Theory of Preliminary Test and Stein‐Type Estimation With Applications
- Estimation and decision for linear systems with elliptical random processes
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