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Spatial Cluster Modelling - Andrew B. Lawson Lawson, Andrew B. David G.T. Denison Denison, David G.T.
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Andrew B. Lawson Lawson, Andrew B. David G.T. Denison Denison, David G.T.:
Spatial Cluster Modelling - gebunden oder broschiert

2002, ISBN: 1584882662

ID: 743107168

[EAN: 9781584882664], Neubuch, [PU: Taylor and Francis(Chapman and Hall/CRC)], (304 pages) Research has generated a number of advances in methods for spatia custer modeing in recent years, particuary in the area of Bayesian custer modeing. Aong with these advances has come an exposion of interest in the potentia appications of this work, especiay in epidemioogy and genome research. In one integrated voume, this book reviews the state-of-the-art in spatia custering and spatia custer modeing, bringing together research and appications previousy scattered throughout the iterature. It begins with an overview of the fied, then presents a series of chapters that iuminate the nature and purpose of custer modeing within different appication areas, incuding astrophysics, epidemioogy, ecoogy, and imaging. The focus then shifts to methods, with discussions on point and object process modeing, perfect samping of custer processes, partitioning in space and space-time, spatia and spatio-tempora process modeing, nonparametric methods for custering, and spatio-tempora custer modeing. Many figures, some in fu coor, compement the text, and a singe section of references cited makes it easy to ocate source materia. Leading speciaists in the fied of custer modeing authored each chapter, and an introduction by the editors to each chapter provides a cohesion not typicay found in contributed works. Spatia Custer Modeing thus offers a singuar opportunity to expore this exciting new fied, understand its techniques, and appy them in your own research.SPATIAL CLUSTER MODELLING: AN OVERVIEW Introduction Historica Deveopment Notation and Mode Deveopment I. POINT PROCESS CLUSTER MODELLING SIGNIFICANCE IN SCALE-SPACE FOR CLUSTERING Introduction Overview New Method Future Directions STATISTICAL INFERENCE FOR COX PROCESSES Introduction Poisson Processes Cox Processes Summary Statistics Parametric Modes of Cox Processes Estimation for Parametric Modes of Cox Processes Prediction Discussion EXTRAPOLATING AND INTERPOLATING SPATIAL PATTERNS Introduction Formuation and Notation Spatia Custer Processes Bayesian Custer Anaysis Summary and Concusion PERFECT SAMPLING FOR POINT PROCESS CLUSTER MODELLING Introduction Bayesian Custer Mode Samping from the Posterior Speciaized Exampes Leukemia Incidence in Upstate New York Redwood Seedings Data BAYESIAN ESTIMATION AND SEGMENTATION OF SPATIAL POINT PROCESSES USING VORONOI TILINGS Introduction Proposed Soution Framework Intensity Estimation Intensity Segmentation Exampes Discussion II. SPATIAL PROCESS CLUSTER MODELLING PARTITION MODELLING Introduction Partition Modes Piazza Road Dataset Spatia Count Data Discussion Further Reading CLUSTER MODELLING FOR DISEASE RATE MAPPING Introduction Statistica Mode Posterior Cacuation Exampe: U.S. Cancer Mortaity Atas Concusions ANALYZING SPATIAL DATA USING SKEW-GAUSSIAN PROCESSES Introduction Skew-Gaussian Processes Rea Data Iustration: Spatia Potentia Data Prediction Discussion ACCOUNTING FOR ABSORPTION LINES IN IMAGES OBTAINED WITH THE CHANDRA X-RAY OBSERVATORY Statistica Chaenges of the Chandra X-Ray Observatory Modeing the Image Absorption Lines Spectra Modes with Absorption Lines Discussion SPATIAL MODELLING OF COUNT DATA: A CASE STUDY IN MODELLING BREEDING BIRD SURVEY DATA ON LARGE SPATIAL DOMAINS Introduction The Poisson Random Effects Mode Resuts Concusion III. SPATIO-TEMPORAL CLUSTER MODELLING MODELLING STRATEGIES FOR SPATIAL-TEMPORAL DATA Introduction Modeing Strategy D-D (Drift-Drift) Modes D-C (Drift-Correation) Modes C-C (Correation-Correation) Modes A Unified Anaysis on the Circe Discussion SPATIO-TEMPORAL PARTITION MODELLING: AN EXAMPLE FROM NEUROPHYSIOLOGY Introduction The Neurophysioogica Experiment The Linear Inverse Soution The Mixture Mode Cassification of the Inverse Soution Discussion SPATIO-TEMPORAL CLUSTER MODELLING OF SMALL AREA HEALTH DATA Introduction Basic Custer Modeing Approaches A Spatio-Tempora Hidden Process Mode Mode Deveopment The Posterior Samping Agorithm Data Exampe: Scottish Birth Abnormaities Discussion REFERENCES INDEX AUTHO

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Spatial Cluster Modelling - Andrew B. Lawson Lawson, Andrew B. David G.T. Denison Denison, David G.T.
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Andrew B. Lawson Lawson, Andrew B. David G.T. Denison Denison, David G.T.:
Spatial Cluster Modelling - gebunden oder broschiert

2002, ISBN: 1584882662

ID: 743107168

[EAN: 9781584882664], Neubuch, [PU: Taylor and Francis(Chapman and Hall/CRC)], (304 pages) Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research. In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal cluster modelling. Many figures, some in full color, complement the text, and a single section of references cited makes it easy to locate source material. Leading specialists in the field of cluster modelling authored each chapter, and an introduction by the editors to each chapter provides a cohesion not typically found in contributed works. Spatial Cluster Modelling thus offers a singular opportunity to explore this exciting new field, understand its techniques, and apply them in your own research.SPATIAL CLUSTER MODELLING: AN OVERVIEW Introduction Historical Development Notation and Model Development I. POINT PROCESS CLUSTER MODELLING SIGNIFICANCE IN SCALE-SPACE FOR CLUSTERING Introduction Overview New Method Future Directions STATISTICAL INFERENCE FOR COX PROCESSES Introduction Poisson Processes Cox Processes Summary Statistics Parametric Models of Cox Processes Estimation for Parametric Models of Cox Processes Prediction Discussion EXTRAPOLATING AND INTERPOLATING SPATIAL PATTERNS Introduction Formulation and Notation Spatial Cluster Processes Bayesian Cluster Analysis Summary and Conclusion PERFECT SAMPLING FOR POINT PROCESS CLUSTER MODELLING Introduction Bayesian Cluster Model Sampling from the Posterior Specialized Examples Leukemia Incidence in Upstate New York Redwood Seedlings Data BAYESIAN ESTIMATION AND SEGMENTATION OF SPATIAL POINT PROCESSES USING VORONOI TILINGS Introduction Proposed Solution Framework Intensity Estimation Intensity Segmentation Examples Discussion II. SPATIAL PROCESS CLUSTER MODELLING PARTITION MODELLING Introduction Partition Models Piazza Road Dataset Spatial Count Data Discussion Further Reading CLUSTER MODELLING FOR DISEASE RATE MAPPING Introduction Statistical Model Posterior Calculation Example: U.S. Cancer Mortality Atlas Conclusions ANALYZING SPATIAL DATA USING SKEW-GAUSSIAN PROCESSES Introduction Skew-Gaussian Processes Real Data Illustration: Spatial Potential Data Prediction Discussion ACCOUNTING FOR ABSORPTION LINES IN IMAGES OBTAINED WITH THE CHANDRA X-RAY OBSERVATORY Statistical Challenges of the Chandra X-Ray Observatory Modeling the Image Absorption Lines Spectral Models with Absorption Lines Discussion SPATIAL MODELLING OF COUNT DATA: A CASE STUDY IN MODELLING BREEDING BIRD SURVEY DATA ON LARGE SPATIAL DOMAINS Introduction The Poisson Random Effects Model Results Conclusion III. SPATIO-TEMPORAL CLUSTER MODELLING MODELLING STRATEGIES FOR SPATIAL-TEMPORAL DATA Introduction Modelling Strategy D-D (Drift-Drift) Models D-C (Drift-Correlation) Models C-C (Correlation-Correlation) Models A Unified Analysis on the Circle Discussion SPATIO-TEMPORAL PARTITION MODELLING: AN EXAMPLE FROM NEUROPHYSIOLOGY Introduction The Neurophysiological Experiment The Linear Inverse Solution The Mixture Model Classification of the Inverse Solution Discussion SPATIO-TEMPORAL CLUSTER MODELLING OF SMALL AREA HEALTH DATA Introduction Basic Cluster Modelling Approaches A Spatio-Temporal Hidden

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Spatial Cluster Modelling - Lawson, Andrew B.; Denison, David G.T.
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SPATIAL CLUSTER MODELLING: AN OVERVIEW Introduction Historical Development Notation and Model Development I. POINT PROCESS CLUSTER MODELLING SIGNIFICANCE IN SCALE-SPACE FOR CLUSTERING Introduction Overview New Method Future Directions STATISTICAL INFERENCE FOR COX PROCESSES Introduction Poisson Processes Cox Processes Summary Statistics Parametric Models of Cox Processes Estimation for Parametric Models of Cox Processes Prediction Discussion EXTRAPOLATING AND INTERPOLATING SPATIAL PATTERNS Introduction Formulation and Notation Spatial Cluster Processes Bayesian Cluster Analysis Summary and Conclusion PERFECT SAMPLING FOR POINT PROCESS CLUSTER MODELLING Introduction Bayesian Cluster Model Sampling from the Posterior Specialized Examples Leukemia Incidence in Upstate New York Redwood Seedlings Data BAYESIAN ESTIMATION AND SEGMENTATION OF SPATIAL POINT PROCESSES USING VORONOI TILINGS Introduction Proposed Solution Framework Intensity Estimation Intensity Segmentation Examples Discussion II. SPATIAL PROCESS CLUSTER MODELLING PARTITION MODELLING Introduction Partition Models Piazza Road Dataset Spatial Count Data Discussion Further Reading CLUSTER MODELLING FOR DISEASE RATE MAPPING Introduction Statistical Model Posterior Calculation Example: U.S. Cancer Mortality Atlas Conclusions ANALYZING SPATIAL DATA USING SKEW-GAUSSIAN PROCESSES Introduction Skew-Gaussian Processes Real Data Illustration: Spatial Potential Data Prediction Discussion ACCOUNTING FOR ABSORPTION LINES IN IMAGES OBTAINED WITH THE CHANDRA X-RAY OBSERVATORY Statistical Challenges of the Chandra X-Ray Observatory Modeling the Image Absorption Lines Spectral Models with Absorption Lines Discussion SPATIAL MODELLING OF COUNT DATA: A CASE STUDY IN MODELLING BREEDING BIRD SURVEY DATA ON LARGE SPATIAL DOMAINS Introduction The Poisson Random Effects Model Results Conclusion III. SPATIO-TEMPORAL CLUSTER MODELLING MODELLING STRATEGIES FOR SPATIAL-TEMPORAL DATA Introduction Modelling Strategy D-D (Drift-Drift) Models D-C (Drift-Correlation) Models C-C (Correlation-Correlation) Models A Unified Analysis on the Circle Discussion SPATIO-TEMPORAL PARTITION MODELLING: AN EXAMPLE FROM NEUROPHYSIOLOGY Introduction The Neurophysiological Experiment The Linear Inverse Solution The Mixture Model Classification of the Inverse Solution Discussion SPATIO-TEMPORAL CLUSTER MODELLING OF SMALL AREA HEALTH DATA Introduction Basic Cluster Modelling Approaches A Spatio-Temporal Hidden Process Model Model Development The Posterior Sampling Algorithm Data Example: Scottish Birth Abnormalities Discussion REFERENCES INDEX AUTHOR INDEX Science Science eBook, CRC Press

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Spatial Cluster Modelling (Monographs on Statistics and Applied Probability)
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Spatial clustering is a topic of growing interest in many disciplines, from geoscience to epidemiology. In recent years, many new advances have appeared, particularly in the area of Bayesian cluster modelling. However, much of this work has been scattered in disparate areas of the literature. This book provides, in one integrated volume, a review of the state-of-the-art in spatial clustering and spatial cluster modelling. Organized in three sections, it includes an overview of the field and its applications Spatial clustering is a topic of growing interest in many disciplines, from geoscience to epidemiology. In recent years, many new advances have appeared, particularly in the area of Bayesian cluster modelling. However, much of this work has been scattered in disparate areas of the literature. This book provides, in one integrated volume, a review of the state-of-the-art in spatial clustering and spatial cluster modelling. Organized in three sections, it includes an overview of the field and its applications, discussions of the theoretical underpinnings of methodology, and explorations of spatio-temporal cluster modelling, all written by leading researchers in the field.

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Spatial Cluster Modelling - Andrew B. Lawson; David G. T. Denison
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2002, ISBN: 9781584882664

ID: 4441955

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Spatial Cluster Modelling
Autor:

Lawson, Andrew; Denison, David

Titel:

Spatial Cluster Modelling

ISBN-Nummer:

Spatial clustering is a topic of growing interest in many disciplines, from geoscience to epidemiology. In recent years, many new advances have appeared, particularly in the area of Bayesian cluster modelling. However, much of this work has been scattered in disparate areas of the literature. This book provides, in one integrated volume, a review of the state-of-the-art in spatial clustering and spatial cluster modelling. Organized in three sections, it includes an overview of the field and its applications, discussions of the theoretical underpinnings of methodology, and explorations of spatio-temporal cluster modelling, all written by leading researchers in the field.

Detailangaben zum Buch - Spatial Cluster Modelling


EAN (ISBN-13): 9781584882664
ISBN (ISBN-10): 1584882662
Gebundene Ausgabe
Erscheinungsjahr: 2002
Herausgeber: CHAPMAN & HALL
304 Seiten
Gewicht: 0,562 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 02.12.2007 11:08:07
Buch zuletzt gefunden am 22.06.2017 09:31:48
ISBN/EAN: 1584882662

ISBN - alternative Schreibweisen:
1-58488-266-2, 978-1-58488-266-4


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