Mixed Models

Beschreibung

A rigorous, self-contained examination of mixed model theory andapplication Mixed modeling is one of the most promising and exciting areasof statistical analysis, enabling the analysis of nontraditional,clustered data that may come in the form of shapes or images. Thisbook provides in-depth mathematical coverage of mixed models'statistical properties and numerical algorithms, as well asapplications such as the analysis of tumor regrowth, shape, andimage. Paying special attention to algorithms and theirimplementations, the book discusses: * Modeling of complex clustered or longitudinal data * Modeling data with multiple sources of variation * Modeling biological variety and heterogeneity * Mixed model as a compromise between the frequentist andBayesian approaches * Mixed model for the penalized log-likelihood * Healthy Akaike Information Criterion (HAIC) * How to cope with parameter multidimensionality * How to solve ill-posed problems including image reconstructionproblems * Modeling of ensemble shapes and images * Statistics of image processing Major results and points of discussion at the end of eachchapter along with "Summary Points" sections make this referencenot only comprehensive but also highly accessible for professionalsand students alike in a broad range of fields such as cancerresearch, computer science, engineering, and industry.

Autor*in

Eugene Demidenko

Themen in »Mixed Models«

Angew. Wahrscheinlichkeitsrechn. u. Statistik / Modelle Applied Probability & Statistics - Models Biostatistics Biostatistik Medical Science Medical Sciences Special Topics Medizin Spezialthemen Medizin Statistics Statistik

Stimmen zu »Mixed Models«

".this book will serve to greatly complement the growingnumber of texts dealing with mixed models and I highly recommendincluding it in one's personal library." (Journal of theAmerican Statistical Association, December 2006) ".an excellent book and it thoroughly covers newdevelopments in mixed models in addition to the classical mixedmodel approaches." (Biometrics, March 2006) "Statisticians would like very much to read this book."(Journal of Statistical Computation and Simulation, January2006) ".I recommend this book and congratulate the author forhis dedication." (Annals of Biomedical Engineering,October 2005) ".has a wealth of information. I recommend this book toanyone working in mixed models." (Journal of BiopharmaceuticalStatistics, July/August 2005) ".a very welcome addition and.a good companion toother mixed models texts." (Statistical Methods in MedicalResearch, Vol. 14, 2005) ".intended for professionals and students in a broad rangeof fields such as cancer research, computer science, engineeringand industry." (Zentralblatt Math, Vol.1055, No.06,2005) "The book is useful for statisticians who are interested inmathematical statistics and those who are interested inapplications." (Mathematical Reviews, 2005e) "Written with the statistician/mathematician in mind, thecomputer engineer will find the content also useful."(E-STREAMS, February 2005)
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