Modelling Longitudinal and Spatially Correlated Data
Timothy G. Gregoire
ISBN 10: 0387982167 ISBN 13: 9780387982168
Editorial: Springer-Verlag New York Inc., 1997
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This item is printed on demand. New copy - Usually dispatched within 5-9 working days. N° de ref. del artículo C9780387982168
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Correlated data arise in numerous contexts across a wide spectrum of subject-matter disciplines. Modeling such data present special challenges and opportunities that have received increasing scrutiny by the statistical community in recent years. In October 1996 a group of 210 statisticians and other scientists assembled on the small island of Nantucket, U. S. A. , to present and discuss new developments relating to Modelling Longitudinal and Spatially Correlated Data: Methods, Applications, and Future Direc tions. Its purpose was to provide a cross-disciplinary forum to explore the commonalities and meaningful differences in the source and treatment of such data. This volume is a compilation of some of the important invited and volunteered presentations made during that conference. The three days and evenings of oral and displayed presentations were arranged into six broad thematic areas. The session themes, the invited speakers and the topics they addressed were as follows: • Generalized Linear Models: Peter McCullagh-"Residual Likelihood in Linear and Generalized Linear Models" • Longitudinal Data Analysis: Nan Laird-"Using the General Linear Mixed Model to Analyze Unbalanced Repeated Measures and Longi tudinal Data" • Spatio---Temporal Processes: David R. Brillinger-"Statistical Analy sis of the Tracks of Moving Particles" • Spatial Data Analysis: Noel A. Cressie-"Statistical Models for Lat tice Data" • Modelling Messy Data: Raymond J. Carroll-"Some Results on Gen eralized Linear Mixed Models with Measurement Error in Covariates" • Future Directions: Peter J.
Reseña del editor: Correlated data arise in numerous contexts across a wide spectrum of subject-matter disciplines. Modeling such data present special challenges and opportunities that have received increasing scrutiny by the statistical community in recent years. In October 1996 a group of 210 statisticians and other scientists assembled on the small island of Nantucket, U. S. A. , to present and discuss new developments relating to Modelling Longitudinal and Spatially Correlated Data: Methods, Applications, and Future Direc tions. Its purpose was to provide a cross-disciplinary forum to explore the commonalities and meaningful differences in the source and treatment of such data. This volume is a compilation of some of the important invited and volunteered presentations made during that conference. The three days and evenings of oral and displayed presentations were arranged into six broad thematic areas. The session themes, the invited speakers and the topics they addressed were as follows: · Generalized Linear Models: Peter McCullagh-"Residual Likelihood in Linear and Generalized Linear Models" · Longitudinal Data Analysis: Nan Laird-"Using the General Linear Mixed Model to Analyze Unbalanced Repeated Measures and Longi tudinal Data" · Spatio---Temporal Processes: David R. Brillinger-"Statistical Analy sis of the Tracks of Moving Particles" · Spatial Data Analysis: Noel A. Cressie-"Statistical Models for Lat tice Data" · Modelling Messy Data: Raymond J. Carroll-"Some Results on Gen eralized Linear Mixed Models with Measurement Error in Covariates" · Future Directions: Peter J.
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Título: Modelling Longitudinal and Spatially ...
Editorial: Springer-Verlag New York Inc.
Año de publicación: 1997
Encuadernación: Paperback / softback
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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Correlated data arise in numerous contexts across a wide spectrum of subject-matter disciplines. Modeling such data present special challenges and opportunities that have received increasing scrutiny by the statistical community in recent years. In October . Nº de ref. del artículo: 5913204
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Taschenbuch. Condición: Neu. Modelling Longitudinal and Spatially Correlated Data | Timothy G. Gregoire (u. a.) | Taschenbuch | x | Englisch | 1997 | Springer | EAN 9780387982168 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 102413383
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Paperback. Condición: new. Paperback. This volume focuses on the statistical treatment of continuous and discrete data measured at different points in time, locations in space, and/or across combined spatio-temporal dimensions. Linear, nonlinear, and generalized linear models and methods are presented, as are new developments to handle messy data. The volume provides an examination of the historical development of approaches to model spatially and temporally correlated data and the ongoing convergence of these methods. The papers are based on ones presented at a conference in Nantucket, Massachusetts in October 1996. This refereed volume includes papers presented at a conference on modeling longitudinal and spatially correlated data. Many of the best researchers in the world presented papers in an area with applications to biostatistics and the environmental sciences. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9780387982168
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ISBN 10: 0387982167
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Correlated data arise in numerous contexts across a wide spectrum of subject-matter disciplines. Modeling such data present special challenges and opportunities that have received increasing scrutiny by the statistical community in recent years. In October 1996 a group of 210 statisticians and other scientists assembled on the small island of Nantucket, U. S. A. , to present and discuss new developments relating to Modelling Longitudinal and Spatially Correlated Data: Methods, Applications, and Future Direc tions. Its purpose was to provide a cross-disciplinary forum to explore the commonalities and meaningful differences in the source and treatment of such data. This volume is a compilation of some of the important invited and volunteered presentations made during that conference. The three days and evenings of oral and displayed presentations were arranged into six broad thematic areas. The session themes, the invited speakers and the topics they addressed were as follows: - Generalized Linear Models: Peter McCullagh-'Residual Likelihood in Linear and Generalized Linear Models' - Longitudinal Data Analysis: Nan Laird-'Using the General Linear Mixed Model to Analyze Unbalanced Repeated Measures and Longi tudinal Data' - Spatio---Temporal Processes: David R. Brillinger-'Statistical Analy sis of the Tracks of Moving Particles' - Spatial Data Analysis: Noel A. Cressie-'Statistical Models for Lat tice Data' - Modelling Messy Data: Raymond J. Carroll-'Some Results on Gen eralized Linear Mixed Models with Measurement Error in Covariates' - Future Directions: Peter J. 420 pp. Englisch. Nº de ref. del artículo: 9780387982168
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Modelling Longitudinal and Spatially Correlated Data
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Springer New York, Springer US Mai 1997, 1997
ISBN 10: 0387982167
ISBN 13: 9780387982168
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Correlated data arise in numerous contexts across a wide spectrum of subject-matter disciplines. Modeling such data present special challenges and opportunities that have received increasing scrutiny by the statistical community in recent years. In October 1996 a group of 210 statisticians and other scientists assembled on the small island of Nantucket, U. S. A. , to present and discuss new developments relating to Modelling Longitudinal and Spatially Correlated Data: Methods, Applications, and Future Direc tions. Its purpose was to provide a cross-disciplinary forum to explore the commonalities and meaningful differences in the source and treatment of such data. This volume is a compilation of some of the important invited and volunteered presentations made during that conference. The three days and evenings of oral and displayed presentations were arranged into six broad thematic areas. The session themes, the invited speakers and the topics they addressed were as follows: ¿ Generalized Linear Models: Peter McCullagh-'Residual Likelihood in Linear and Generalized Linear Models' ¿ Longitudinal Data Analysis: Nan Laird-'Using the General Linear Mixed Model to Analyze Unbalanced Repeated Measures and Longi tudinal Data' ¿ Spatio---Temporal Processes: David R. Brillinger-'Statistical Analy sis of the Tracks of Moving Particles' ¿ Spatial Data Analysis: Noel A. Cressie-'Statistical Models for Lat tice Data' ¿ Modelling Messy Data: Raymond J. Carroll-'Some Results on Gen eralized Linear Mixed Models with Measurement Error in Covariates' ¿ Future Directions: Peter J.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 420 pp. Englisch. Nº de ref. del artículo: 9780387982168
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