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02442cam a2200481 4500 |
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PPN195467868 |
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http://www.sudoc.fr/195467868 |
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20190627114400.0 |
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|a 978-1-439-86683-2
|b hbk. : alk. paper
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|a 1-439-86683-X
|b hbk. : alk. paper
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|a US
|b 2013026053
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|a (OCoLC)676728383
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|a 17795291
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|a LC-17795291
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|a 20160930h20142014k y0frey0103 ba
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|a eng
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|a US
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|a a a 001|y
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|a r
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|6 z01
|c txt
|2 rdacontent
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|6 z01
|a i#
|b xxxe##
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|c n
|2 rdamedia
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|6 z01
|a n
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1 |
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|a Richly parameterized linear models
|e additive, time series, and spatial models using random effects
|f James S. Hodges,...
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| 210 |
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|a Boca Raton (Fla.)
|c CRC Press
|d cop. 2014
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| 215 |
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|a 1 vol. (XXXVIII-431 p.)
|c ill.
|d 24 cm
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2 |
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|a Texts in statistical science
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| 320 |
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|a Bibliogr. p. 413-424. Index
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|a "This book covers a wide range of statistical models, including hierarchical, hierarchical generalized linear, linear mixed, dynamic linear, smoothing, spatial, and longitudinal. It presents a framework for expressing these richly parameterized models together as well as tools for exploring and interpreting the results of fitting the models to data. It extends the standard theory of linear models and illustrates the advantages and disadvantages of various theories. The book also examines surprising or undesirable results arising in the use of the models to analyze real data sets from collaborative research"
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| 359 |
2 |
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|b I. Mixed Linear Models : Syntax, Theory, and Methods
|b II. Richly Parameterized Models as Mixed Linear Models
|b III. From Linear Models to Richly Parameterized Models : Mean Structure
|b IV. Beyond Linear Models : Variance Structure
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| 410 |
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| |
|0 188876650
|t Texts in statistical science
|x 2380-5161
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| 606 |
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|3 PPN02739381X
|a Analyse de régression
|2 rameau
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| 606 |
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|3 PPN027674134
|a Modèles linéaires (statistique)
|2 rameau
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| 676 |
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|a 519.5/36
|v 23
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| 700 |
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|3 PPN195468104
|a Hodges
|b James S.
|4 070
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| 801 |
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|a FR
|b Abes
|c 20161018
|g AFNOR
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|b DLC
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|a 850404
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