Imputed quantile tensor regression for near-sited spatial-temporal data-Reference-Cited by-同舟云学术

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Imputed quantile tensor regression for near-sited spatial-temporal data

Published:2023-06 Issue: Volume:182 Page:107713
ISSN:0167-9473
Container-title:Computational Statistics & Data Analysis
language:en
Short-container-title:Computational Statistics & Data Analysis

Author:

Liang Jinwen,Härdle Wolfgang Karl,Tian Maozai^ORCID

Funder

Fundamental Research Funds for the Central Universities

Renmin University of China

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference32 articles.

1. A singular value thresholding algorithm for matrix completion;Cai;SIAM J. Optim.,2008

2. The power of convex relaxation: near-optimal matrix completion;Candès;IEEE Trans. Inf. Theory,2010

3. Bayesian temporal factorization for multidimensional time series prediction;Chen;IEEE Trans. Pattern Anal. Mach. Intell.,2021

4. A nonconvex low-rank tensor completion model for spatiotemporal traffic data imputation;Chen;Transp. Res., Part C, Emerg. Technol.,2020

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Tensor quantile regression with low-rank tensor train estimation;The Annals of Applied Statistics;2024-06-01

2. Imputed quantile vector autoregressive model for multivariate spatial–temporal data;Statistical Analysis and Data Mining: The ASA Data Science Journal;2024-01-25

3. A Novel Truncated Normal Tensor Completion Method for Multi-Source Fusion Data;Mathematics;2024-01-09

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