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010   $a9786613202918
010   $a0-470-09484-2
010   $a0-470-09483-4
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100   $a20110325d2011      uy         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aMaximum likelihood estimation and inference $ewith examples in R, SAS, and ADMB /$fRussell B. Millar
205   $a1st ed.
210   $aChichester, Sussex, U.K. ;$aHoboken, N.J. $cWiley$d2011
215   $a1 online resource (378 p.)
225 1 $aStatistics in practice
300   $aDescription based upon print version of record.
311   $a0-470-09482-6 
320   $aIncludes bibliographical references and index.
327   $apt. 1. Preliminaries -- pt. 2. Pragmatics -- pt. 3. Theoretical foundations.
330   $a"Applied Likelihood Methods provides an accessible and practical introduction to likelihood modeling, supported by examples and software. The book features applications from a range of disciplines, including statistics, medicine, biology, and ecology. The methods are implemented in SAS--the most widely used statistical software package--and the data sets and SAS code are provided on a Web site, enabling the reader to use the methods to solve problems in their own work. This book serves as an ideal text for applied scientists and researchers and graduate students of statistics"--$cProvided by publisher.
410  0$aStatistics in practice.
606   $aEstimation theory
606   $aChance$xMathematical models
606   $aR (Computer program language)
615  0$aEstimation theory.
615  0$aChance$xMathematical models.
615  0$aR (Computer program language).
676   $a519.5/44
686   $aMAT029000$2bisacsh
686   $aSK 830$2rvk
700   $aMillar$b R. B$g(Russell B.)$0928072
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910133223203321
996   $aMaximum likelihood estimation and inference$92085653
997   $aUNINA