Density estimation for mixed Euclidean and non-Euclidean data in the presence of measurement error-Reference-Cited by-同舟云学术

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Density estimation for mixed Euclidean and non-Euclidean data in the presence of measurement error

Published:2023-01 Issue: Volume:193 Page:105125
ISSN:0047-259X
Container-title:Journal of Multivariate Analysis
language:en
Short-container-title:Journal of Multivariate Analysis

Author:

Jeon Jeong Min^ORCID,Van Keilegom Ingrid

Funder

Ministry of Science, ICT and Future Planning

European Research Council

National Research Foundation of Korea

European Resuscitation Council

Horizon 2020

Publisher

Elsevier BV

Subject

Statistics, Probability and Uncertainty,Numerical Analysis,Statistics and Probability

Reference61 articles.

1. A multivariate Linnik distribution;Anderson;Statist. Probab. Lett.,1992

2. Probability on Compact Lie Groups;Applebaum,2014

3. Density deconvolution under general assumptions on the distribution of measurement errors;Belomestny;Ann. Statist.,2021

4. The Laplace operator on normal homogeneous Riemannian manifolds;Berestovskiĭ;Siberian Adv. Math.,2010

5. Flexible parametric approach to classical measurement error variance estimation without auxiliary data;Bertrand;Biometrics,2019

Cited by 2 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. A transportation Revitalization index prediction model based on Spatial-Temporal attention mechanism;Advanced Engineering Informatics;2024-08

2. Errors-in-variables regression for mixed Euclidean and non-Euclidean predictors;Journal of Nonparametric Statistics;2024-07-24

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