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Generalized Linear Mixed Models: Modern Concepts, Methods and Applications (Chapman & Hall/CRC Texts in Statistical Science)
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1498755569 ISBN 13: 9781498755566
Language: English
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Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models (Chapman & Hall/CRC Texts in Statistical Science)
Published by Chapman and Hall/CRC, 2005
ISBN 10: 158488424X ISBN 13: 9781584884248
Language: English
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Add to basketCondition: Used: Good. Occasion - Bon Etat - Generalized linear and mixed models (2001) - Poche.
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Linear and Generalized Linear Mixed Models and Their Applications (Springer Series in Statistics)
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Direct Likelihood Approximations for Generalized Linear Mixed Models: An Adaptive Approach
Published by VDM Verlag Dr. Müller, 2010
ISBN 10: 3639286936 ISBN 13: 9783639286939
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Generalized Linear Mixed Models with Applications in Agriculture and Biology
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Multivariate Generalized Linear Mixed Models Using R
Published by CRC Press 2011-05-20, 2011
ISBN 10: 1439813264 ISBN 13: 9781439813263
Language: English
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Repeated Measures Design With Generalized Linear Mixed Models for Randomized Controlled Trials
Published by Chapman and Hall/CRC, 2017
ISBN 10: 1498747892 ISBN 13: 9781498747899
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Generalized, Linear, and Mixed Models : Second Edition
Published by John Wiley and Sons, Hoboken, 2008
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Add to basketCondition: Fine. Second Edition. Hardcover : pp. [iv] xxv [xxvi] 384 [408] : blue and white boards. Wiley Series in Probability and Statistics.
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![Stock image for Regression: Models, Methods and Applications [Englisch] [Gebundene Ausgabe] Mathematik Informatik Mathematik Wirtschaft Lexika Generalized Linear Models linear regression mixed models Regression Statistik Semiparametric Regression spatial regression Wirtschaftsstatistik Ludwig Fahrmeir (Autor), Thomas Kneib (Autor), Stefan Lang (Autor), Brian Marx (Autor) for sale by BUCHSERVICE / ANTIQUARIAT Lars Lutzer](https://pictures.abebooks.com/isbn/9783642343322-us-300.jpg)
Regression: Models, Methods and Applications [Englisch] [Gebundene Ausgabe] Mathematik Informatik Mathematik Wirtschaft Lexika Generalized Linear Models linear regression mixed models Regression Statistik Semiparametric Regression spatial regression Wirtschaftsstatistik Ludwig Fahrmeir (Autor), Thomas Kneib (Autor), Stefan Lang (Autor), Brian Marx (Autor)
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Add to basketHardcover. Condition: gut. 2013. The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through many real data examples and case studies. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. Thus, the book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written on an intermediate mathematical level and assumes only knowledge of basic probability, calculus, and statistics. The most important definitions and statements are concisely summarized in boxes. Two appendices describe required matrix algebra, as well as elements of probability calculus and statistical inference. Autor: Ludwig Fahrmeir is Professor emeritus at the Department of Statistics at Ludwig-Maximilians-University Munich. From 1995 to 2006 he was speaker of the Collaborative Research Center 'Statistical Analysis of Discrete Data', supported financially by the German National Science Foundation. His main research interests are semiparametric regression, longitudinal data analysis and spatial statistics, with applications ranging from social science and risk management to public health and neuroscience. - Thomas Kneib is Professor for Statistics at Georg August University Göttingen, Germany, where he is speaker of the interdisciplinary Centre for Statistics and a Research Training Group on "Scaling Problems in Statistics". He received his PhD in Statistics at Ludwig-Maximilians-University Munich and, during his PostDoc phase, has been Visiting Professor for Applied Statistics at the University of Ulm and Substitute Professor for Statistics at Georg-August-University Göttingen. From 2009 until 2011 he has been Professor for Applied Statistics at Carl von Ossietzky University Oldenburg. His main research interests include semiparametric regression, spatial statistics and quantile regression. - Stefan Lang is Professor for Applied Statistics at University of Innsbruck, Austria. He received his PhD at Ludwig-Maximilians-University Munich. From 2005 to 2006 he has been Professor for Statistics at University of Leipzig. He is currently editor of Advances of Statistical Analysis and Associate Editor of Statistical Modelling. His main research interests include semiparametric and spatial regression, multilevel modelling and complex Bayesian models, with applications among others in environmetrics, marketing science, real estate and actuarial science. - Brian D. Marx is a full professor in the Department of Experimental Statisitics at Louisiana State University. His main research interests include P-spline smoothiing, ill-conditioned regression problems, and high-dimensional chemometric applications. He is currently serving as coordinating editor for the journal Statistical Modelling and is past chair of the Statistical Modelling Society. Content: Introduction.- Regression Models.- The Classical Linear Model.- Extensions of the Classical Linear Model.- Generalized Linear Models.- Categorical Regression Models.- Mixed Models.- Nonparametric Regression.- Structured Additive Regression.- Quantile Regression.- A Matrix Algebra.- B Probability Calculus and Statistical Inference.- Bibliography.- Index. Zusatzinfo XIV, 698 p. Verlagsort Berlin Sprache englisch Maße 155 x 235 mm Mathematik / Informatik Mathematik Wirtschaft Lexika Generalized Linear Models linear regression mixed models Regression Statistik Semiparametric Regression spatial regression Wirtschaftsstatistik ISBN-10 3-642-34332-5 / 3642343325 ISBN-13 978-3-642-34332-2 / 9783642343322 In englischer Sprache. 650 pages. 15,6 x 3,8 x 23,4 cm.
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Add to basketPaperback. Condition: Brand New. 271 pages. 9.00x6.00x0.63 inches. In Stock.
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Wiley Series in Probability and Statistics Generalized, linear, and mixed Models
Published by Wiley Inter-Science, 2001
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Wiley Series in Probability and Statistics Generalized, linear, and mixed Models
Published by Wiley Inter-Science, 2001
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Generalized Linear Mixed Models Modern Concepts Methods and Applications
Published by Taylor & Francis, 2013
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Add to basketpaperback. Condition: New. Paperback. Pub Date: 2013-03-01 Pages: 165 Language: Chinese Publisher: Science Press. LLC Linear and generalized linear mixed models and statistical diagnostics system introduces the basic theory of linear mixed models and generalized linear mixed models and method. It includes two models parameter estimation. hypothesis testing. confidence regions and statistical diagnose problems. Statistical analysis is focused on the diagnosis of the two models. using probe data deletion problem studied .
