Posted by **interes** at March 4, 2015

English | ISBN: 1441983414, 1441983422 | edition 2011 | PDF | 512 pages | 4 mb

Posted by **interes** at Jan. 28, 2014

English | ISBN: 1441983414, 1441983422 | edition 2011 | PDF | 512 pages | 4 mb

This book provides a theoretical foundation for the analysis of discrete data such as count and binary data in the longitudinal setup. Unlike the existing books, this book uses a class of auto-correlation structures to model the longitudinal correlations for the repeated discrete data that accommodates all possible Gaussian type auto-correlation models as special cases including the equi-correlation models.

Posted by **tanas.olesya** at Jan. 3, 2015

English | June 16, 2000 | ISBN: 0387950273 | 579 Pages | PDF | 39 MB

This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure.

Posted by **fdts** at Sept. 14, 2013

by Geert Molenberghs, Geert Verbeke

English | 2005 | ISBN: 0387251448 | 687 pages | PDF | 5.3 MB

Posted by **BUGSY** at May 19, 2015

English | Aug 19, 2009 | ISBN: 1420064266 | 279 Pages | PDF | 2 MB

The First Book Dedicated to This Class of Longitudinal Models. Although antedependence models are particularly useful for modeling longitudinal data that exhibit serial correlation, few books adequately cover these models.

Posted by **interes** at July 1, 2014

English | 2012 | ISBN-10: 0891181822 | 283 pages | PDF | 21,7 MB

Generalized Linear Mixed Models in the Agricultural and Natural ResourcesSciences provides readers with an understanding and appreciation for the design and analysis of mixed models for non-normally distributed data. It is the only publication of its kind directed specifically toward the agricultural and natural resources sciences audience.

Posted by **Book-er** at July 1, 2012

English | 2006-10-25 | ISBN: 0415316812 | 244 pages | PDF | 8 MB

In both the physical and social sciences, there are now available large spatial data sets with detailed local information. Global models for analyzing these data are not suitable for investigating local variations; consequently, local models are the subject of much recent research. Collecting a variety of models into a single reference, Local Models for Spatial Analysis explains in detail a variety of approaches for analyzing univariate and multivariate spatial data.

Posted by **puliraja** at June 18, 2009

Walter Zucchini, Iain L. MacDonald | Chapman & Hall/CRC | 2009-04-28 | ISBN:1584885734 | Pages: 269 | PDF | 5.3MB

This book illustrates the wonderful flexibility of HMMs as general-purpose models for time series data. It presents an accessible overview of HMMs for analyzing time series data, from continuous-valued, circular, and multivariate series to binary data, bounded and unbounded counts, and categorical observations. It explores a variety of applications in animal behavior, finance, epidemiology, climatology, and sociology. The authors discuss how to employ the freely available computing environment R to carry out computations for parameter estimation, model selection and checking, decoding, and forecasting. They provide all of the data sets analyzed in the text online.

Posted by **enmoys** at June 9, 2016

2014 | 424 Pages | ISBN: 1433817152 | PDF | 5 MB

Posted by **insetes** at Jan. 13, 2016

2012 | 275 Pages | ISBN: 1439872864 | PDF | 3 MB