On generalized moment identity and its applications: a unified approach
In this paper, we obtain a generalized moment identity for the case when the distributions of the random variables are not necessarily purely discrete or absolutely continuous. The proposed identity is useful to find the generator which has been used for the approximation of distributions by Stein&#...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Kattumannil, Sudheesh K [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Rechteinformationen: |
Nutzungsrecht: © 2015 Taylor & Francis 2015 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Statistics - Abingdon, Oxon [u.a.] : Taylor & Francis, 1985, 50(2016), 5, Seite 1149-1160 |
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| Übergeordnetes Werk: |
volume:50 ; year:2016 ; number:5 ; pages:1149-1160 |
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| DOI / URN: |
10.1080/02331888.2015.1119150 |
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| 520 | |a In this paper, we obtain a generalized moment identity for the case when the distributions of the random variables are not necessarily purely discrete or absolutely continuous. The proposed identity is useful to find the generator which has been used for the approximation of distributions by Stein's method. Apparently, a new approach is discussed for the approximation of distributions by Stein's method. We bring the characterization based on the relationship between conditional expectations and hazard measure in our unified framework. As an application, a new lower bound to the mean-squared error is obtained and it is compared with Bayesian Cramer-Rao bound. | ||
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| 650 | 4 | |a Bayesian Cramer-Rao bound | |
| 650 | 4 | |a moment identity | |
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10.1080/02331888.2015.1119150 doi PQ20161201 (DE-627)OLC1982304561 (DE-599)GBVOLC1982304561 (PRQ)c1262-a6af537ab5f7d508126a528bb58b3183a940d29c86026afbdb301e0b4e3d955e0 (KEY)0092533020160000050000501149ongeneralizedmomentidentityanditsapplicationsaunif DE-627 ger DE-627 rakwb eng 15 27 310 DNB 510 AVZ Kattumannil, Sudheesh K verfasserin aut On generalized moment identity and its applications: a unified approach 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this paper, we obtain a generalized moment identity for the case when the distributions of the random variables are not necessarily purely discrete or absolutely continuous. The proposed identity is useful to find the generator which has been used for the approximation of distributions by Stein's method. Apparently, a new approach is discussed for the approximation of distributions by Stein's method. We bring the characterization based on the relationship between conditional expectations and hazard measure in our unified framework. As an application, a new lower bound to the mean-squared error is obtained and it is compared with Bayesian Cramer-Rao bound. Nutzungsrecht: © 2015 Taylor & Francis 2015 Stein's identity conditional variance unbiased estimation reliability analysis Bayesian Cramer-Rao bound moment identity Dewan, Isha oth Enthalten in Statistics Abingdon, Oxon [u.a.] : Taylor & Francis, 1985 50(2016), 5, Seite 1149-1160 (DE-627)130630934 (DE-600)798366-9 (DE-576)016136500 0233-1888 nnns volume:50 year:2016 number:5 pages:1149-1160 http://dx.doi.org/10.1080/02331888.2015.1119150 Volltext http://www.tandfonline.com/doi/abs/10.1080/02331888.2015.1119150 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_2004 GBV_ILN_2010 GBV_ILN_4036 AR 50 2016 5 1149-1160 |
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10.1080/02331888.2015.1119150 doi PQ20161201 (DE-627)OLC1982304561 (DE-599)GBVOLC1982304561 (PRQ)c1262-a6af537ab5f7d508126a528bb58b3183a940d29c86026afbdb301e0b4e3d955e0 (KEY)0092533020160000050000501149ongeneralizedmomentidentityanditsapplicationsaunif DE-627 ger DE-627 rakwb eng 15 27 310 DNB 510 AVZ Kattumannil, Sudheesh K verfasserin aut On generalized moment identity and its applications: a unified approach 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this paper, we obtain a generalized moment identity for the case when the distributions of the random variables are not necessarily purely discrete or absolutely continuous. The proposed identity is useful to find the generator which has been used for the approximation of distributions by Stein's method. Apparently, a new approach is discussed for the approximation of distributions by Stein's method. We bring the characterization based on the relationship between conditional expectations and hazard measure in our unified framework. As an application, a new lower bound to the mean-squared error is obtained and it is compared with Bayesian Cramer-Rao bound. Nutzungsrecht: © 2015 Taylor & Francis 2015 Stein's identity conditional variance unbiased estimation reliability analysis Bayesian Cramer-Rao bound moment identity Dewan, Isha oth Enthalten in Statistics Abingdon, Oxon [u.a.] : Taylor & Francis, 1985 50(2016), 5, Seite 1149-1160 (DE-627)130630934 (DE-600)798366-9 (DE-576)016136500 0233-1888 nnns volume:50 year:2016 number:5 pages:1149-1160 http://dx.doi.org/10.1080/02331888.2015.1119150 Volltext http://www.tandfonline.com/doi/abs/10.1080/02331888.2015.1119150 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_2004 GBV_ILN_2010 GBV_ILN_4036 AR 50 2016 5 1149-1160 |
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In this paper, we obtain a generalized moment identity for the case when the distributions of the random variables are not necessarily purely discrete or absolutely continuous. The proposed identity is useful to find the generator which has been used for the approximation of distributions by Stein's method. Apparently, a new approach is discussed for the approximation of distributions by Stein's method. We bring the characterization based on the relationship between conditional expectations and hazard measure in our unified framework. As an application, a new lower bound to the mean-squared error is obtained and it is compared with Bayesian Cramer-Rao bound. |
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In this paper, we obtain a generalized moment identity for the case when the distributions of the random variables are not necessarily purely discrete or absolutely continuous. The proposed identity is useful to find the generator which has been used for the approximation of distributions by Stein's method. Apparently, a new approach is discussed for the approximation of distributions by Stein's method. We bring the characterization based on the relationship between conditional expectations and hazard measure in our unified framework. As an application, a new lower bound to the mean-squared error is obtained and it is compared with Bayesian Cramer-Rao bound. |
| abstract_unstemmed |
In this paper, we obtain a generalized moment identity for the case when the distributions of the random variables are not necessarily purely discrete or absolutely continuous. The proposed identity is useful to find the generator which has been used for the approximation of distributions by Stein's method. Apparently, a new approach is discussed for the approximation of distributions by Stein's method. We bring the characterization based on the relationship between conditional expectations and hazard measure in our unified framework. As an application, a new lower bound to the mean-squared error is obtained and it is compared with Bayesian Cramer-Rao bound. |
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| title_short |
On generalized moment identity and its applications: a unified approach |
| url |
http://dx.doi.org/10.1080/02331888.2015.1119150 http://www.tandfonline.com/doi/abs/10.1080/02331888.2015.1119150 |
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