Opening book details…
Can I read Modelling Longitudinal and Spatially Correlated Data (Lecture Notes in Statistics 122) on EtoBox?
Modelling Longitudinal and Spatially Correlated Data (Lecture Notes in Statistics 122) by Peter McCullagh (auth.), Timothy G. Gregoire, David R. Brillinger, Peter J. Diggle, Estelle Russek-Cohen, William G. Warren, Russell D. Wolfinger (eds.) is a nonfiction available to read on EtoBox.
What is Modelling Longitudinal and Spatially Correlated Data (Lecture Notes in Statistics 122) about?
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 Rep
Who reads Modelling Longitudinal and Spatially Correlated Data (Lecture Notes in Statistics 122)?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Peter McCullagh (auth.), Timothy G. Gregoire, David R. Brillinger, Peter J. Diggle, Estelle Russek-Cohen, William G. Warren, Russell D. Wolfinger (eds.)
- Publisher
- Springer-Verlag New York
- Published
- 1997
- Language
- EN
- ISBN
- 9781461206996
- Category
- nonfiction
- Subjects
- Mathematics, Engineering, Medical
Other editions & translations
More by Peter McCullagh (auth.), Timothy G. Gregoire, David R. Brillinger, Peter J. Diggle, Estelle Russek-Cohen, William G. Warren, Russell D. Wolfinger (eds.)
Similar books
- Modelling Longitudinal Data — Robert E. Weiss (2005)
- Metric Methods For Analyzing Partially Ranked Data (lecture Notes In Statistics) — Douglas E. Critchlow (auth.) (1985)
- Linear Mixed Models for Longitudinal Data (Springer Series in Statistics) — Geert Molenberghs, Geert Verbeke (auth.) (2000)
- Parametric and Nonparametric Inference from Record-Breaking Data (Lecture Notes in Statistics, 172) — Sneh Gulati, William J. Padgett (auth.) (2003)
- Longitudinal Data Analysis (Wiley Series in Probability and Statistics) — Donald R Hedeker; Robert D Gibbons (2006)
- Statistical Methods in Psychiatry and Related Fields: Longitudinal, Clustered, and Other Repeated Measures Data (Chapman & Hall/CRC Interdisciplinary Statistics) — Ralitza Gueorguieva (2017)
