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Książka Modelling Longitudinal and Spatially Correlated Data Timothy G. Gregoire

Modelling Longitudinal and Spatially Correlated Data

Autor: Timothy G. Gregoire
Język: Angielski
Oprawa: Miękka
Wydawca: Springer-Verlag New York Inc.
Dostępność: Dostępna u dostawcy
Wysyłamy za 5-8 dni
429.36 zł
Correlated data arise in numerous contexts across a wide spectrum of subject-matter disciplines. Mod...

Informacje o książce

Autor
Timothy G. Gregoire
Język
Angielski
Oprawa
Książka - Miękka
Data wydania
1997
strony
402
EAN
9780387982168
ISBN
0387982167
Enbook ID
04067064
Wydawca
Springer-Verlag New York Inc.
Waga
1290
Wymiary
155 x 235 x 23

Pełny opis

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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