Finding upper-level sets in cellular surface data using echelons and saTScan
Abstract Across a spectrum of contemporary contexts from public health to landscape ecology and natural resources, there is need for objective determination of elevated occurrence in phenomena such as disease incidence and biodiversity. Occurrences of such phenomena constitute response surfaces, but...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Myers, Wayne L. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2006 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC 2006 |
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| Übergeordnetes Werk: |
Enthalten in: Environmental and ecological statistics - Kluwer Academic Publishers, 1994, 13(2006), 4 vom: Dez., Seite 379-390 |
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| Übergeordnetes Werk: |
volume:13 ; year:2006 ; number:4 ; month:12 ; pages:379-390 |
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| DOI / URN: |
10.1007/s10651-006-0018-4 |
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OLC2066584479 |
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| 520 | |a Abstract Across a spectrum of contemporary contexts from public health to landscape ecology and natural resources, there is need for objective determination of elevated occurrence in phenomena such as disease incidence and biodiversity. Occurrences of such phenomena constitute response surfaces, but data regarding the surface is typically acquired in a cellular framework. The cells may comprise a regular grid, or may be of irregular shapes such as counties in which statistics are collected. Echelons are a topologically based approach to systematic determination of spatial structure in a step surface. Spatial scan statistics are a probability-based approach to the same issue when interest lies in a rate variable. Here we examine the use of echelons both separately and in conjunction with the SaTScan implementation of spatial scan statistics for purposes of determination and visualization of upper-level sets. Consideration is given to both conventional geographic space and to the cellular pseudo-space of contingency tables for ordered categorical variables. | ||
| 650 | 4 | |a Surface structure | |
| 650 | 4 | |a Upper level sets | |
| 650 | 4 | |a Topologies | |
| 650 | 4 | |a Echelons | |
| 650 | 4 | |a SaTScan | |
| 650 | 4 | |a Ordered contingency tables | |
| 700 | 1 | |a Kurihara, Koji |4 aut | |
| 700 | 1 | |a Patil, Ganapati P. |4 aut | |
| 700 | 1 | |a Vraney, Ryan |4 aut | |
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10.1007/s10651-006-0018-4 doi (DE-627)OLC2066584479 (DE-He213)s10651-006-0018-4-p DE-627 ger DE-627 rakwb eng 310 VZ Myers, Wayne L. verfasserin aut Finding upper-level sets in cellular surface data using echelons and saTScan 2006 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2006 Abstract Across a spectrum of contemporary contexts from public health to landscape ecology and natural resources, there is need for objective determination of elevated occurrence in phenomena such as disease incidence and biodiversity. Occurrences of such phenomena constitute response surfaces, but data regarding the surface is typically acquired in a cellular framework. The cells may comprise a regular grid, or may be of irregular shapes such as counties in which statistics are collected. Echelons are a topologically based approach to systematic determination of spatial structure in a step surface. Spatial scan statistics are a probability-based approach to the same issue when interest lies in a rate variable. Here we examine the use of echelons both separately and in conjunction with the SaTScan implementation of spatial scan statistics for purposes of determination and visualization of upper-level sets. Consideration is given to both conventional geographic space and to the cellular pseudo-space of contingency tables for ordered categorical variables. Surface structure Upper level sets Topologies Echelons SaTScan Ordered contingency tables Kurihara, Koji aut Patil, Ganapati P. aut Vraney, Ryan aut Enthalten in Environmental and ecological statistics Kluwer Academic Publishers, 1994 13(2006), 4 vom: Dez., Seite 379-390 (DE-627)188856781 (DE-600)1284261-8 (DE-576)067290140 1352-8505 nnns volume:13 year:2006 number:4 month:12 pages:379-390 https://doi.org/10.1007/s10651-006-0018-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-FOR SSG-OLC-IBL GBV_ILN_70 GBV_ILN_2004 GBV_ILN_4116 AR 13 2006 4 12 379-390 |
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10.1007/s10651-006-0018-4 doi (DE-627)OLC2066584479 (DE-He213)s10651-006-0018-4-p DE-627 ger DE-627 rakwb eng 310 VZ Myers, Wayne L. verfasserin aut Finding upper-level sets in cellular surface data using echelons and saTScan 2006 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2006 Abstract Across a spectrum of contemporary contexts from public health to landscape ecology and natural resources, there is need for objective determination of elevated occurrence in phenomena such as disease incidence and biodiversity. Occurrences of such phenomena constitute response surfaces, but data regarding the surface is typically acquired in a cellular framework. The cells may comprise a regular grid, or may be of irregular shapes such as counties in which statistics are collected. Echelons are a topologically based approach to systematic determination of spatial structure in a step surface. Spatial scan statistics are a probability-based approach to the same issue when interest lies in a rate variable. Here we examine the use of echelons both separately and in conjunction with the SaTScan implementation of spatial scan statistics for purposes of determination and visualization of upper-level sets. Consideration is given to both conventional geographic space and to the cellular pseudo-space of contingency tables for ordered categorical variables. Surface structure Upper level sets Topologies Echelons SaTScan Ordered contingency tables Kurihara, Koji aut Patil, Ganapati P. aut Vraney, Ryan aut Enthalten in Environmental and ecological statistics Kluwer Academic Publishers, 1994 13(2006), 4 vom: Dez., Seite 379-390 (DE-627)188856781 (DE-600)1284261-8 (DE-576)067290140 1352-8505 nnns volume:13 year:2006 number:4 month:12 pages:379-390 https://doi.org/10.1007/s10651-006-0018-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-FOR SSG-OLC-IBL GBV_ILN_70 GBV_ILN_2004 GBV_ILN_4116 AR 13 2006 4 12 379-390 |
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10.1007/s10651-006-0018-4 doi (DE-627)OLC2066584479 (DE-He213)s10651-006-0018-4-p DE-627 ger DE-627 rakwb eng 310 VZ Myers, Wayne L. verfasserin aut Finding upper-level sets in cellular surface data using echelons and saTScan 2006 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2006 Abstract Across a spectrum of contemporary contexts from public health to landscape ecology and natural resources, there is need for objective determination of elevated occurrence in phenomena such as disease incidence and biodiversity. Occurrences of such phenomena constitute response surfaces, but data regarding the surface is typically acquired in a cellular framework. The cells may comprise a regular grid, or may be of irregular shapes such as counties in which statistics are collected. Echelons are a topologically based approach to systematic determination of spatial structure in a step surface. Spatial scan statistics are a probability-based approach to the same issue when interest lies in a rate variable. Here we examine the use of echelons both separately and in conjunction with the SaTScan implementation of spatial scan statistics for purposes of determination and visualization of upper-level sets. Consideration is given to both conventional geographic space and to the cellular pseudo-space of contingency tables for ordered categorical variables. Surface structure Upper level sets Topologies Echelons SaTScan Ordered contingency tables Kurihara, Koji aut Patil, Ganapati P. aut Vraney, Ryan aut Enthalten in Environmental and ecological statistics Kluwer Academic Publishers, 1994 13(2006), 4 vom: Dez., Seite 379-390 (DE-627)188856781 (DE-600)1284261-8 (DE-576)067290140 1352-8505 nnns volume:13 year:2006 number:4 month:12 pages:379-390 https://doi.org/10.1007/s10651-006-0018-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-FOR SSG-OLC-IBL GBV_ILN_70 GBV_ILN_2004 GBV_ILN_4116 AR 13 2006 4 12 379-390 |
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10.1007/s10651-006-0018-4 doi (DE-627)OLC2066584479 (DE-He213)s10651-006-0018-4-p DE-627 ger DE-627 rakwb eng 310 VZ Myers, Wayne L. verfasserin aut Finding upper-level sets in cellular surface data using echelons and saTScan 2006 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2006 Abstract Across a spectrum of contemporary contexts from public health to landscape ecology and natural resources, there is need for objective determination of elevated occurrence in phenomena such as disease incidence and biodiversity. Occurrences of such phenomena constitute response surfaces, but data regarding the surface is typically acquired in a cellular framework. The cells may comprise a regular grid, or may be of irregular shapes such as counties in which statistics are collected. Echelons are a topologically based approach to systematic determination of spatial structure in a step surface. Spatial scan statistics are a probability-based approach to the same issue when interest lies in a rate variable. Here we examine the use of echelons both separately and in conjunction with the SaTScan implementation of spatial scan statistics for purposes of determination and visualization of upper-level sets. Consideration is given to both conventional geographic space and to the cellular pseudo-space of contingency tables for ordered categorical variables. Surface structure Upper level sets Topologies Echelons SaTScan Ordered contingency tables Kurihara, Koji aut Patil, Ganapati P. aut Vraney, Ryan aut Enthalten in Environmental and ecological statistics Kluwer Academic Publishers, 1994 13(2006), 4 vom: Dez., Seite 379-390 (DE-627)188856781 (DE-600)1284261-8 (DE-576)067290140 1352-8505 nnns volume:13 year:2006 number:4 month:12 pages:379-390 https://doi.org/10.1007/s10651-006-0018-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-FOR SSG-OLC-IBL GBV_ILN_70 GBV_ILN_2004 GBV_ILN_4116 AR 13 2006 4 12 379-390 |
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Finding upper-level sets in cellular surface data using echelons and saTScan |
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Abstract Across a spectrum of contemporary contexts from public health to landscape ecology and natural resources, there is need for objective determination of elevated occurrence in phenomena such as disease incidence and biodiversity. Occurrences of such phenomena constitute response surfaces, but data regarding the surface is typically acquired in a cellular framework. The cells may comprise a regular grid, or may be of irregular shapes such as counties in which statistics are collected. Echelons are a topologically based approach to systematic determination of spatial structure in a step surface. Spatial scan statistics are a probability-based approach to the same issue when interest lies in a rate variable. Here we examine the use of echelons both separately and in conjunction with the SaTScan implementation of spatial scan statistics for purposes of determination and visualization of upper-level sets. Consideration is given to both conventional geographic space and to the cellular pseudo-space of contingency tables for ordered categorical variables. © Springer Science+Business Media, LLC 2006 |
| abstractGer |
Abstract Across a spectrum of contemporary contexts from public health to landscape ecology and natural resources, there is need for objective determination of elevated occurrence in phenomena such as disease incidence and biodiversity. Occurrences of such phenomena constitute response surfaces, but data regarding the surface is typically acquired in a cellular framework. The cells may comprise a regular grid, or may be of irregular shapes such as counties in which statistics are collected. Echelons are a topologically based approach to systematic determination of spatial structure in a step surface. Spatial scan statistics are a probability-based approach to the same issue when interest lies in a rate variable. Here we examine the use of echelons both separately and in conjunction with the SaTScan implementation of spatial scan statistics for purposes of determination and visualization of upper-level sets. Consideration is given to both conventional geographic space and to the cellular pseudo-space of contingency tables for ordered categorical variables. © Springer Science+Business Media, LLC 2006 |
| abstract_unstemmed |
Abstract Across a spectrum of contemporary contexts from public health to landscape ecology and natural resources, there is need for objective determination of elevated occurrence in phenomena such as disease incidence and biodiversity. Occurrences of such phenomena constitute response surfaces, but data regarding the surface is typically acquired in a cellular framework. The cells may comprise a regular grid, or may be of irregular shapes such as counties in which statistics are collected. Echelons are a topologically based approach to systematic determination of spatial structure in a step surface. Spatial scan statistics are a probability-based approach to the same issue when interest lies in a rate variable. Here we examine the use of echelons both separately and in conjunction with the SaTScan implementation of spatial scan statistics for purposes of determination and visualization of upper-level sets. Consideration is given to both conventional geographic space and to the cellular pseudo-space of contingency tables for ordered categorical variables. © Springer Science+Business Media, LLC 2006 |
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Finding upper-level sets in cellular surface data using echelons and saTScan |
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https://doi.org/10.1007/s10651-006-0018-4 |
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Kurihara, Koji Patil, Ganapati P. Vraney, Ryan |
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10.1007/s10651-006-0018-4 |
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