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http://bura.brunel.ac.uk/handle/2438/29289Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Chen, P | - |
| dc.contributor.author | Nourdin, I | - |
| dc.contributor.author | Xu, L | - |
| dc.contributor.author | Yang, X | - |
| dc.date.accessioned | 2024-07-03T08:56:17Z | - |
| dc.date.available | 2024-07-03T08:56:17Z | - |
| dc.date.issued | 2023-05-04 | - |
| dc.identifier | ORCiD: Xiaochuan Yang https://orcid.org/0000-0003-2435-4615 | - |
| dc.identifier | arXiv:1911.12917v2 [math.PR] | - |
| dc.identifier.citation | Chen, P. et al. (2024) 'Multivariate Stable Approximation by Stein’s Method', Journal of Theoretical Probability, 37 (1), pp. 446 - 488. doi: 10.1007/s10959-023-01244-x. | en_US |
| dc.identifier.issn | 0894-9840 | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/29289 | - |
| dc.description | Data Availability: Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study. | en_US |
| dc.description | Mathematics Subject Classification :60E07; 60E17; 60F05; 60G52. | - |
| dc.description | The article version archived on this institutional repository is the accepted manuscript available online at: arXiv:1911.12917v2 [math.PR] (https://arxiv.org/abs/1911.12917v2) under the working title, 'Multivariate stable approximation in Wasserstein distance by Stein's method'. It has been certified by peer review. | - |
| dc.description.abstract | By a delicate analysis for the Stein's equation associated to the α-stable law approximation with α ∈ (0,2), we prove a quantitative stable central limit theorem in Wasserstein type distance, which generalizes the results in the series of work (Chen et al. in J Theor Probab 34(3):1382–1407, 2021; Chen et al. in J Theor Probab 35(2):1137–1186 2022; Xu in Ann Appl Probab 29(1):458–504, 2019) from the univariate case to the multiple variate case. From an explicit computation for Pareto’s distribution, we see that the rate of our approximation is sharp. The analysis of the Stein’s equation is new and has independent interest. | en_US |
| dc.description.sponsorship | P. Chen is supported by the NSF of Jiangsu Province Grant BK20220867 and the Initial Scientific Research Fund of Young Teachers in Nanjing University of Aeronautics and Astronautics (1008-YAH21111). L. Xu is partially supported by NSFC No. 12071499, Macao S.A.R Grant FDCT 0090/2019/A2 and University of Macau Grant MYRG2020-00039-FST. | en_US |
| dc.format.extent | 446 - 488 | - |
| dc.format.medium | Print-Electronic | - |
| dc.language | Enlish | - |
| dc.language.iso | en_US | en_US |
| dc.publisher | Springer Nature | en_US |
| dc.relation.uri | https://arxiv.org/abs/1911.12917v2 | - |
| dc.rights | Copyright© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s10959-023-01244-x (see: https://www.springernature.com/gp/open-research/policies/journal-policies). | - |
| dc.rights.uri | https://www.springernature.com/gp/open-research/policies/journal-policies | - |
| dc.subject | multivariate α-stable approximation | en_US |
| dc.subject | Stein’s method | en_US |
| dc.subject | generalized central limit theorem | en_US |
| dc.subject | rate of convergence | en_US |
| dc.subject | Wasserstein(-type) distance | en_US |
| dc.subject | fractional Laplacian | en_US |
| dc.title | Multivariate Stable Approximation by Stein’s Method | en_US |
| dc.title.alternative | Multivariate stable approximation in Wasserstein distance by Stein's method | en_US |
| dc.type | Article | en_US |
| dc.date.dateAccepted | 2023-01-24 | - |
| dc.identifier.doi | https://doi.org/10.1007/s10959-023-01244-x | - |
| dc.relation.isPartOf | Journal of Theoretical Probability | - |
| pubs.issue | 1 | - |
| pubs.publication-status | Published | - |
| pubs.volume | 37 | - |
| dc.identifier.eissn | 1572-9230 | - |
| dc.rights.holder | The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature | - |
| Appears in Collections: | Dept of Mathematics Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Copyright© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s10959-023-01244-x (see: https://www.springernature.com/gp/open-research/policies/journal-policies). | 423.89 kB | Adobe PDF | View/Open |
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