Mixed Models Theory and Applications

Author/creator Demidenko, Eugene, 1948- Author
Format Electronic
Publication InfoWiley-Interscience [Imprint] Hoboken : John Wiley & Sons, Incorporated
Description736 p. ill 24.050 x 016.150 cm.
Supplemental ContentFull text available from eBooks on EBSCOhost
Subjects

SeriesStatistics in Practice Ser.
Summary Annotation A rigorous, self-contained examination of mixed model theory and application<p>Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in-depth mathematical coverage of mixed models&#8217; statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image.</p><p>Paying special attention to algorithms and their implementations, the book discusses:</p><ul><li>Modeling of complex clustered or longitudinal data</li><li>Modeling data with multiple sources of variation</li><li>Modeling biological variety and heterogeneity</li><li>Mixed model as a compromise between the frequentist and Bayesian approaches</li><li>Mixed model for the penalized log-likelihood</li><li>Healthy Akaike Information Criterion (HAIC)</li><li>How to cope with parameter multidimensionality</li><li>How to solve ill-posed problems including image reconstruction problems</li><li>Modeling of ensemble shapes and images</li><li>Statistics of image processing</li></ul><p>Major results and points of discussion at the end of each chapter along with "Summary Points" sections make this reference not only comprehensive but also highly accessible for professionals and students alike in a broad range of fields such as cancer research, computer science, engineering, and industry.</p>
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2004045643
ISBN9780471601616
ISBN0471601616 (Trade Cloth) Active Record
Standard identifier# 9780471601616
Stock number00028608

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