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Mixed models : = theory and applicat...
~
Demidenko, Eugene, (1948-.)
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Mixed models : = theory and applications with R /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Mixed models :/ Eugene Demidenko.
其他題名:
theory and applications with R /
作者:
Demidenko, Eugene,
出版者:
Hoboken, New Jersey :John Wiley & Sons, Inc., : 2013.,
面頁冊數:
xxvii, 717 p. :ill. ;26 cm.
標題:
Analysis of variance. -
ISBN:
9781118091579 (hbk.) :
Mixed models : = theory and applications with R /
Demidenko, Eugene,1948-.
Mixed models :
theory and applications with R /Eugene Demidenko. - 2nd ed. - Hoboken, New Jersey :John Wiley & Sons, Inc.,2013. - xxvii, 717 p. :ill. ;26 cm. - Wiley series in probability and statistics.. - Wiley series in probability and statistics..
Includes bibliographical references (p. 681-709) and index.
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' statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. The new edition includes significant updating, over 300 exercises, stimulating chapter projects and model simulations, inclusion of R subroutines, and a revised text format. The target audience continues to be graduate students and researchers. An author-maintained web site is available with solutions to exercises and a compendium of relevant data sets--
ISBN: 9781118091579 (hbk.) :US129.95
LCCN: 2013001306Subjects--Topical Terms:
516400
Analysis of variance.
LC Class. No.: QA279 / .D457 2013
Mixed models : = theory and applications with R /
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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' statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. The new edition includes significant updating, over 300 exercises, stimulating chapter projects and model simulations, inclusion of R subroutines, and a revised text format. The target audience continues to be graduate students and researchers. An author-maintained web site is available with solutions to exercises and a compendium of relevant data sets--
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