Residual as Linear Sum of Matrix Determinants in Multiway Contingency Tables
Abstract A Pearson residual is defined as a residual between an observed value and expected one of each cell in a contingency table, which measures the degree of statistical dependence of two attribute-value pairs corresponding to the cell. This paper shows that this residual is decomposed into a li...
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| Autor*in: |
Tsumoto, Shusaku [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2011 |
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| Schlagwörter: |
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| Anmerkung: |
© the authors 2011 |
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| Übergeordnetes Werk: |
Enthalten in: International journal of computational intelligence systems - Paris : Atlantis Press, 2008, 4(2011), 5 vom: 01. Sept., Seite 1080-1089 |
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| Übergeordnetes Werk: |
volume:4 ; year:2011 ; number:5 ; day:01 ; month:09 ; pages:1080-1089 |
| Links: |
|---|
| DOI / URN: |
10.2991/ijcis.2011.4.5.31 |
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10.2991/ijcis.2011.4.5.31 doi (DE-627)SPR054189659 (SPR)ijcis.2011.4.5.31-e DE-627 ger DE-627 rakwb eng Tsumoto, Shusaku verfasserin aut Residual as Linear Sum of Matrix Determinants in Multiway Contingency Tables 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © the authors 2011 Abstract A Pearson residual is defined as a residual between an observed value and expected one of each cell in a contingency table, which measures the degree of statistical dependence of two attribute-value pairs corresponding to the cell. This paper shows that this residual is decomposed into a linear sum of determinants of 2 × 2 subtables, which means that the geometrical nature of the residuals can be viewed from grasmmanian algebra. Pearson Residual (dpeaa)DE-He213 Determinants (dpeaa)DE-He213 Multiway Contingency Table (dpeaa)DE-He213 Information Granules (dpeaa)DE-He213 Hirano, Shoji aut Enthalten in International journal of computational intelligence systems Paris : Atlantis Press, 2008 4(2011), 5 vom: 01. Sept., Seite 1080-1089 (DE-627)777781514 (DE-600)2754752-8 1875-6883 nnns volume:4 year:2011 number:5 day:01 month:09 pages:1080-1089 https://dx.doi.org/10.2991/ijcis.2011.4.5.31 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2011 5 01 09 1080-1089 |
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10.2991/ijcis.2011.4.5.31 doi (DE-627)SPR054189659 (SPR)ijcis.2011.4.5.31-e DE-627 ger DE-627 rakwb eng Tsumoto, Shusaku verfasserin aut Residual as Linear Sum of Matrix Determinants in Multiway Contingency Tables 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © the authors 2011 Abstract A Pearson residual is defined as a residual between an observed value and expected one of each cell in a contingency table, which measures the degree of statistical dependence of two attribute-value pairs corresponding to the cell. This paper shows that this residual is decomposed into a linear sum of determinants of 2 × 2 subtables, which means that the geometrical nature of the residuals can be viewed from grasmmanian algebra. Pearson Residual (dpeaa)DE-He213 Determinants (dpeaa)DE-He213 Multiway Contingency Table (dpeaa)DE-He213 Information Granules (dpeaa)DE-He213 Hirano, Shoji aut Enthalten in International journal of computational intelligence systems Paris : Atlantis Press, 2008 4(2011), 5 vom: 01. Sept., Seite 1080-1089 (DE-627)777781514 (DE-600)2754752-8 1875-6883 nnns volume:4 year:2011 number:5 day:01 month:09 pages:1080-1089 https://dx.doi.org/10.2991/ijcis.2011.4.5.31 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2011 5 01 09 1080-1089 |
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10.2991/ijcis.2011.4.5.31 doi (DE-627)SPR054189659 (SPR)ijcis.2011.4.5.31-e DE-627 ger DE-627 rakwb eng Tsumoto, Shusaku verfasserin aut Residual as Linear Sum of Matrix Determinants in Multiway Contingency Tables 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © the authors 2011 Abstract A Pearson residual is defined as a residual between an observed value and expected one of each cell in a contingency table, which measures the degree of statistical dependence of two attribute-value pairs corresponding to the cell. This paper shows that this residual is decomposed into a linear sum of determinants of 2 × 2 subtables, which means that the geometrical nature of the residuals can be viewed from grasmmanian algebra. Pearson Residual (dpeaa)DE-He213 Determinants (dpeaa)DE-He213 Multiway Contingency Table (dpeaa)DE-He213 Information Granules (dpeaa)DE-He213 Hirano, Shoji aut Enthalten in International journal of computational intelligence systems Paris : Atlantis Press, 2008 4(2011), 5 vom: 01. Sept., Seite 1080-1089 (DE-627)777781514 (DE-600)2754752-8 1875-6883 nnns volume:4 year:2011 number:5 day:01 month:09 pages:1080-1089 https://dx.doi.org/10.2991/ijcis.2011.4.5.31 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2011 5 01 09 1080-1089 |
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10.2991/ijcis.2011.4.5.31 doi (DE-627)SPR054189659 (SPR)ijcis.2011.4.5.31-e DE-627 ger DE-627 rakwb eng Tsumoto, Shusaku verfasserin aut Residual as Linear Sum of Matrix Determinants in Multiway Contingency Tables 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © the authors 2011 Abstract A Pearson residual is defined as a residual between an observed value and expected one of each cell in a contingency table, which measures the degree of statistical dependence of two attribute-value pairs corresponding to the cell. This paper shows that this residual is decomposed into a linear sum of determinants of 2 × 2 subtables, which means that the geometrical nature of the residuals can be viewed from grasmmanian algebra. Pearson Residual (dpeaa)DE-He213 Determinants (dpeaa)DE-He213 Multiway Contingency Table (dpeaa)DE-He213 Information Granules (dpeaa)DE-He213 Hirano, Shoji aut Enthalten in International journal of computational intelligence systems Paris : Atlantis Press, 2008 4(2011), 5 vom: 01. Sept., Seite 1080-1089 (DE-627)777781514 (DE-600)2754752-8 1875-6883 nnns volume:4 year:2011 number:5 day:01 month:09 pages:1080-1089 https://dx.doi.org/10.2991/ijcis.2011.4.5.31 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2011 5 01 09 1080-1089 |
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10.2991/ijcis.2011.4.5.31 doi (DE-627)SPR054189659 (SPR)ijcis.2011.4.5.31-e DE-627 ger DE-627 rakwb eng Tsumoto, Shusaku verfasserin aut Residual as Linear Sum of Matrix Determinants in Multiway Contingency Tables 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © the authors 2011 Abstract A Pearson residual is defined as a residual between an observed value and expected one of each cell in a contingency table, which measures the degree of statistical dependence of two attribute-value pairs corresponding to the cell. This paper shows that this residual is decomposed into a linear sum of determinants of 2 × 2 subtables, which means that the geometrical nature of the residuals can be viewed from grasmmanian algebra. Pearson Residual (dpeaa)DE-He213 Determinants (dpeaa)DE-He213 Multiway Contingency Table (dpeaa)DE-He213 Information Granules (dpeaa)DE-He213 Hirano, Shoji aut Enthalten in International journal of computational intelligence systems Paris : Atlantis Press, 2008 4(2011), 5 vom: 01. Sept., Seite 1080-1089 (DE-627)777781514 (DE-600)2754752-8 1875-6883 nnns volume:4 year:2011 number:5 day:01 month:09 pages:1080-1089 https://dx.doi.org/10.2991/ijcis.2011.4.5.31 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2011 5 01 09 1080-1089 |
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residual as linear sum of matrix determinants in multiway contingency tables |
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Residual as Linear Sum of Matrix Determinants in Multiway Contingency Tables |
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Abstract A Pearson residual is defined as a residual between an observed value and expected one of each cell in a contingency table, which measures the degree of statistical dependence of two attribute-value pairs corresponding to the cell. This paper shows that this residual is decomposed into a linear sum of determinants of 2 × 2 subtables, which means that the geometrical nature of the residuals can be viewed from grasmmanian algebra. © the authors 2011 |
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Abstract A Pearson residual is defined as a residual between an observed value and expected one of each cell in a contingency table, which measures the degree of statistical dependence of two attribute-value pairs corresponding to the cell. This paper shows that this residual is decomposed into a linear sum of determinants of 2 × 2 subtables, which means that the geometrical nature of the residuals can be viewed from grasmmanian algebra. © the authors 2011 |
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Abstract A Pearson residual is defined as a residual between an observed value and expected one of each cell in a contingency table, which measures the degree of statistical dependence of two attribute-value pairs corresponding to the cell. This paper shows that this residual is decomposed into a linear sum of determinants of 2 × 2 subtables, which means that the geometrical nature of the residuals can be viewed from grasmmanian algebra. © the authors 2011 |
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