Distribution’s template estimate with Wasserstein metrics
In this paper, we tackle the problem of comparing distributions of random variables and defining a mean pattern between a sample of random events. Using barycenters of measures in the Wasserstein space, we propose an iterative version as an estimation of the mean distribution. Moreover, when the dis...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Boissard, Emmanuel [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Rechteinformationen: |
Nutzungsrecht: © Copyright 2015 Bernoulli Society for Mathematical Statistics and Probability |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
Enthalten in: Bernoulli - The Hague : International Statistical Institute, 1995, 21(2015), 2, Seite 740-759 |
|---|---|
| Übergeordnetes Werk: |
volume:21 ; year:2015 ; number:2 ; pages:740-759 |
| Links: |
|---|
| DOI / URN: |
10.3150/13-BEJ585 |
|---|
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| 520 | |a In this paper, we tackle the problem of comparing distributions of random variables and defining a mean pattern between a sample of random events. Using barycenters of measures in the Wasserstein space, we propose an iterative version as an estimation of the mean distribution. Moreover, when the distributions are a common measure warped by a centered random operator, then the barycenter enables to recover this distribution template. | ||
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10.3150/13-BEJ585 doi PQ20160617 (DE-627)OLC1959945696 (DE-599)GBVOLC1959945696 (PRQ)c909-2d2b0b7e096d3befa1fee2577681c6c7e0a4942d50ca605c503c564ed7e359c10 (KEY)0246191920150000021000200740distributionstemplateestimatewithwassersteinmetric DE-627 ger DE-627 rakwb eng 510 DNB Boissard, Emmanuel verfasserin aut Distribution’s template estimate with Wasserstein metrics 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this paper, we tackle the problem of comparing distributions of random variables and defining a mean pattern between a sample of random events. Using barycenters of measures in the Wasserstein space, we propose an iterative version as an estimation of the mean distribution. Moreover, when the distributions are a common measure warped by a centered random operator, then the barycenter enables to recover this distribution template. Nutzungsrecht: © Copyright 2015 Bernoulli Society for Mathematical Statistics and Probability template estimation Fréchet mean Wasserstein distance Le Gouic, Thibaut oth Loubes, Jean-Michel oth Enthalten in Bernoulli The Hague : International Statistical Institute, 1995 21(2015), 2, Seite 740-759 (DE-627)190371269 (DE-600)1287087-0 (DE-576)04995802X 1350-7265 nnns volume:21 year:2015 number:2 pages:740-759 http://dx.doi.org/10.3150/13-BEJ585 Volltext http://projecteuclid.org/euclid.bj/1429624959 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_31 GBV_ILN_70 GBV_ILN_2002 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2012 GBV_ILN_2088 GBV_ILN_2409 GBV_ILN_4027 GBV_ILN_4036 GBV_ILN_4193 GBV_ILN_4310 GBV_ILN_4311 AR 21 2015 2 740-759 |
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Distribution’s template estimate with Wasserstein metrics |
| abstract |
In this paper, we tackle the problem of comparing distributions of random variables and defining a mean pattern between a sample of random events. Using barycenters of measures in the Wasserstein space, we propose an iterative version as an estimation of the mean distribution. Moreover, when the distributions are a common measure warped by a centered random operator, then the barycenter enables to recover this distribution template. |
| abstractGer |
In this paper, we tackle the problem of comparing distributions of random variables and defining a mean pattern between a sample of random events. Using barycenters of measures in the Wasserstein space, we propose an iterative version as an estimation of the mean distribution. Moreover, when the distributions are a common measure warped by a centered random operator, then the barycenter enables to recover this distribution template. |
| abstract_unstemmed |
In this paper, we tackle the problem of comparing distributions of random variables and defining a mean pattern between a sample of random events. Using barycenters of measures in the Wasserstein space, we propose an iterative version as an estimation of the mean distribution. Moreover, when the distributions are a common measure warped by a centered random operator, then the barycenter enables to recover this distribution template. |
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| container_issue |
2 |
| title_short |
Distribution’s template estimate with Wasserstein metrics |
| url |
http://dx.doi.org/10.3150/13-BEJ585 http://projecteuclid.org/euclid.bj/1429624959 |
| remote_bool |
false |
| author2 |
Le Gouic, Thibaut Loubes, Jean-Michel |
| author2Str |
Le Gouic, Thibaut Loubes, Jean-Michel |
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| author2_role |
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| doi_str |
10.3150/13-BEJ585 |
| up_date |
2024-07-03T19:24:45.115Z |
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7.401967 |