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  • Search: subject:"tensor data"
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Year of publication
Subject
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Tensor data 2 Bayesian estimation 1 Central dimension folding subspace 1 Central subspace 1 Covariance estimation 1 Decomposition method 1 Dekompositionsverfahren 1 Gibbs sampling 1 Hauptkomponentenanalyse 1 Principal component analysis 1 Sliced inverse regression 1 Stein’s loss 1 Sufficient dimension reduction 1 Tensor decomposition 1 Theorie 1 Theory 1 singular value and canonical polyadic decompositions 1 tensor data 1
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Online availability
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Undetermined 2 Free 1
Type of publication
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Article 2 Book / Working Paper 1
Type of publication (narrower categories)
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Arbeitspapier 1 Graue Literatur 1 Non-commercial literature 1 Working Paper 1
Language
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Undetermined 2 English 1
Author
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Babii, Andrii 1 Cook, R. Dennis 1 Ding, Shanshan 1 Gerard, David 1 Ghysels, Eric 1 Hoff, Peter 1 Pan, Junsu 1
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Published in...
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Journal of Multivariate Analysis 2 CEA_372Bayes working paper series 1
Source
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RePEc 2 ECONIS (ZBW) 1
Showing 1 - 3 of 3
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Tensor principal component analysis
Babii, Andrii; Ghysels, Eric; Pan, Junsu - 2023
Persistent link: https://www.econbiz.de/10014284126
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Equivariant minimax dominators of the MLE in the array normal model
Gerard, David; Hoff, Peter - In: Journal of Multivariate Analysis 137 (2015) C, pp. 32-49
Inference about dependence in a multiway data array can be made using the array normal model, which corresponds to the class of multivariate normal distributions with separable covariance matrices. Maximum likelihood and Bayesian methods for inference in the array normal model have appeared in...
Persistent link: https://www.econbiz.de/10011263459
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Tensor sliced inverse regression
Ding, Shanshan; Cook, R. Dennis - In: Journal of Multivariate Analysis 133 (2015) C, pp. 216-231
Sliced inverse regression (SIR) is a widely used non-parametric method for supervised dimension reduction. Conventional SIR mainly tackles simple data structure but is inappropriate for data with array (tensor)-valued predictors. Such data are commonly encountered in modern biomedical imaging...
Persistent link: https://www.econbiz.de/10011116235
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