Evaluation of the Covariance Matrix of Estimated Resonance Parameters
In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Becker, B. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014transfer abstract |
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| Umfang: |
3 |
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Enthalten in: Understanding the occurrence of a wavy wear track on elastomeric materials - Khafidh, M. ELSEVIER, 2018, a journal devoted to compilations and evaluations of experimental and theoretical results in nuclear physics, Orlando, Fla |
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| Übergeordnetes Werk: |
volume:118 ; year:2014 ; pages:381-383 ; extent:3 |
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| DOI / URN: |
10.1016/j.nds.2014.04.086 |
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| 520 | |a In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. | ||
| 520 | |a In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. | ||
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| 700 | 1 | |a Volev, K. |4 oth | |
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10.1016/j.nds.2014.04.086 doi GBVA2014001000006.pica (DE-627)ELV017173175 (ELSEVIER)S0090-3752(14)00116-1 DE-627 ger DE-627 rakwb eng 530 530 DE-600 670 VZ 52.12 bkl Becker, B. verfasserin aut Evaluation of the Covariance Matrix of Estimated Resonance Parameters 2014transfer abstract 3 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. Capote, R. oth Kopecky, S. oth Massimi, C. oth Schillebeeckx, P. oth Sirakov, I. oth Volev, K. oth Enthalten in Academic Press Khafidh, M. ELSEVIER Understanding the occurrence of a wavy wear track on elastomeric materials 2018 a journal devoted to compilations and evaluations of experimental and theoretical results in nuclear physics Orlando, Fla (DE-627)ELV000001120 volume:118 year:2014 pages:381-383 extent:3 https://doi.org/10.1016/j.nds.2014.04.086 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 52.12 Tribologie VZ AR 118 2014 381-383 3 045F 530 |
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10.1016/j.nds.2014.04.086 doi GBVA2014001000006.pica (DE-627)ELV017173175 (ELSEVIER)S0090-3752(14)00116-1 DE-627 ger DE-627 rakwb eng 530 530 DE-600 670 VZ 52.12 bkl Becker, B. verfasserin aut Evaluation of the Covariance Matrix of Estimated Resonance Parameters 2014transfer abstract 3 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. Capote, R. oth Kopecky, S. oth Massimi, C. oth Schillebeeckx, P. oth Sirakov, I. oth Volev, K. oth Enthalten in Academic Press Khafidh, M. ELSEVIER Understanding the occurrence of a wavy wear track on elastomeric materials 2018 a journal devoted to compilations and evaluations of experimental and theoretical results in nuclear physics Orlando, Fla (DE-627)ELV000001120 volume:118 year:2014 pages:381-383 extent:3 https://doi.org/10.1016/j.nds.2014.04.086 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 52.12 Tribologie VZ AR 118 2014 381-383 3 045F 530 |
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10.1016/j.nds.2014.04.086 doi GBVA2014001000006.pica (DE-627)ELV017173175 (ELSEVIER)S0090-3752(14)00116-1 DE-627 ger DE-627 rakwb eng 530 530 DE-600 670 VZ 52.12 bkl Becker, B. verfasserin aut Evaluation of the Covariance Matrix of Estimated Resonance Parameters 2014transfer abstract 3 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. Capote, R. oth Kopecky, S. oth Massimi, C. oth Schillebeeckx, P. oth Sirakov, I. oth Volev, K. oth Enthalten in Academic Press Khafidh, M. ELSEVIER Understanding the occurrence of a wavy wear track on elastomeric materials 2018 a journal devoted to compilations and evaluations of experimental and theoretical results in nuclear physics Orlando, Fla (DE-627)ELV000001120 volume:118 year:2014 pages:381-383 extent:3 https://doi.org/10.1016/j.nds.2014.04.086 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 52.12 Tribologie VZ AR 118 2014 381-383 3 045F 530 |
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10.1016/j.nds.2014.04.086 doi GBVA2014001000006.pica (DE-627)ELV017173175 (ELSEVIER)S0090-3752(14)00116-1 DE-627 ger DE-627 rakwb eng 530 530 DE-600 670 VZ 52.12 bkl Becker, B. verfasserin aut Evaluation of the Covariance Matrix of Estimated Resonance Parameters 2014transfer abstract 3 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. Capote, R. oth Kopecky, S. oth Massimi, C. oth Schillebeeckx, P. oth Sirakov, I. oth Volev, K. oth Enthalten in Academic Press Khafidh, M. ELSEVIER Understanding the occurrence of a wavy wear track on elastomeric materials 2018 a journal devoted to compilations and evaluations of experimental and theoretical results in nuclear physics Orlando, Fla (DE-627)ELV000001120 volume:118 year:2014 pages:381-383 extent:3 https://doi.org/10.1016/j.nds.2014.04.086 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 52.12 Tribologie VZ AR 118 2014 381-383 3 045F 530 |
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10.1016/j.nds.2014.04.086 doi GBVA2014001000006.pica (DE-627)ELV017173175 (ELSEVIER)S0090-3752(14)00116-1 DE-627 ger DE-627 rakwb eng 530 530 DE-600 670 VZ 52.12 bkl Becker, B. verfasserin aut Evaluation of the Covariance Matrix of Estimated Resonance Parameters 2014transfer abstract 3 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. Capote, R. oth Kopecky, S. oth Massimi, C. oth Schillebeeckx, P. oth Sirakov, I. oth Volev, K. oth Enthalten in Academic Press Khafidh, M. ELSEVIER Understanding the occurrence of a wavy wear track on elastomeric materials 2018 a journal devoted to compilations and evaluations of experimental and theoretical results in nuclear physics Orlando, Fla (DE-627)ELV000001120 volume:118 year:2014 pages:381-383 extent:3 https://doi.org/10.1016/j.nds.2014.04.086 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 52.12 Tribologie VZ AR 118 2014 381-383 3 045F 530 |
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Evaluation of the Covariance Matrix of Estimated Resonance Parameters |
| abstract |
In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. |
| abstractGer |
In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. |
| abstract_unstemmed |
In the resonance region nuclear resonance parameters are mostly obtained by a least square adjustment of a model to experimental data. Derived parameters can be mutually correlated through the adjustment procedure as well as through common experimental or model uncertainties. In this contribution we investigate four different methods to propagate the additional covariance caused by experimental or model uncertainties into the evaluation of the covariance matrix of the estimated parameters: (1) including the additional covariance into the experimental covariance matrix based on calculated or theoretical estimates of the data; (2) including the uncertainty affected parameter in the adjustment procedure; (3) evaluation of the full covariance matrix by Monte Carlo sampling of the common parameter; and (4) retroactively including the additional covariance by using the marginalization procedure of Habert et al. |
| collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U |
| title_short |
Evaluation of the Covariance Matrix of Estimated Resonance Parameters |
| url |
https://doi.org/10.1016/j.nds.2014.04.086 |
| remote_bool |
true |
| author2 |
Capote, R. Kopecky, S. Massimi, C. Schillebeeckx, P. Sirakov, I. Volev, K. |
| author2Str |
Capote, R. Kopecky, S. Massimi, C. Schillebeeckx, P. Sirakov, I. Volev, K. |
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| author2_role |
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| doi_str |
10.1016/j.nds.2014.04.086 |
| up_date |
2024-07-06T21:18:17.719Z |
| _version_ |
1803866024412446720 |
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