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010 a| 2013950378;

020 a| 9781461486862 (hbk);

020 a| 1461486866 (hbk);

020 z| 1461486874 (ebk.);

020 z| 9781461486879 (ebk.);

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100 1 a| Marin, Jean-Michel.;

245 10 a| Bayesian essentials with Rh| [electronic resource] /c| Jean-Michel Marin, Christian P. Robert.;

250 a| Second edition.;

260 a| New York :b| Springer,c| [2014];

300 a| xiv, 296 pages :b| illustrations (some color) ;c| 24 cm.;

490 1 a| Springer Texts in Statistics,x| 1431-875X;

504 a| Includes bibliographical references (pages 287-290) and index.;

505 0 a| User's manual -- Normal models -- Regression and variable selection -- Generalized linear models -- Capture-recapture experiments -- Mixture models -- Time series -- Image analysis.;

506 a| Available only to authorized users.;

520 a| This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical and philosophical justifications. Readers are empowered to participate in the real-life data analysis situations depicted here from the beginning. The stakes are high and the reader determines the outcome. Special attention is paid to the derivation of prior distributions in each case and specific reference solutions are given for each of the models. Similarly, computational details are worked out to lead the reader towards an effective programming of the methods given in the book. In particular, all R codes are discussed with enough detail to make them readily understandable and expandable.;

530 a| Also available online.;

538 a| Mode of access: World Wide Web;

650 0 a| Bayesian statistical decision theory.;

650 0 a| R (Computer program language);

655 0 a| Electronic books.;

700 1 a| Robert, Christian P.,d| 1961-;

830 0 a| Springer texts in statistics.;

949 a| CLICK ON WEB ADDRESSw| ASISh| JOYNER188;

856 40 z| Full text available from Springer Nature - Springer Mathematics and Statistics eBooks 2014 English Internationalu| https://go.openathens.net/redirector/ecu.edu?url=https%3A%2F%2Flink.springer.com%2F10.1007%2F978-1-4614-8687-9;

856 40 z| Full text available from Springer Booksu| https://go.openathens.net/redirector/ecu.edu?url=https%3A%2F%2Flink.springer.com%2F10.1007%2F978-1-4614-8687-9;

947 a| (OCoLC)ocn859186504;

949 a| CLICK ON WEB ADDRESSw| ASISh| HSL77;

949 a| CLICK ON WEB ADDRESSw| ASISh| JMUSIC60;

596 a| 1 3 4;

998 a| 3985862;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 3985862-1001l| JNETm| JOYNERr| Ys| Yt| JNESSBKu| 1/1/2016x| EBOOKz| JERESOURCE;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 3985862-2001l| HSLELECm| HSLr| Ys| Yt| HEBKu| 1/1/2016x| EBOOKz| HERESOURCE;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 3985862-3001l| MNETm| JMUSICr| Ys| Yt| MNESSBKu| 1/1/2016x| EBOOKz| JERESOURCE;

Bayesian essentials with R / Jean-Michel Marin, Christian P. Robert.

Author/creator	Marin, Jean-Michel
Other author	Robert, Christian P., 1961-
Format	Electronic
Edition	Second edition.
Publication Info	New York : Springer, [2014]
Description	xiv, 296 pages : illustrations (some color) ; 24 cm.
Supplemental Content	Full text available from Springer Nature - Springer Mathematics and Statistics eBooks 2014 English International
Supplemental Content	Full text available from Springer Books
Subjects	Bayesian statistical decision theory. R (Computer program language)

Series	Springer Texts in Statistics, 1431-875X Springer texts in statistics.
Contents	User's manual -- Normal models -- Regression and variable selection -- Generalized linear models -- Capture-recapture experiments -- Mixture models -- Time series -- Image analysis.
Abstract	This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical and philosophical justifications. Readers are empowered to participate in the real-life data analysis situations depicted here from the beginning. The stakes are high and the reader determines the outcome. Special attention is paid to the derivation of prior distributions in each case and specific reference solutions are given for each of the models. Similarly, computational details are worked out to lead the reader towards an effective programming of the methods given in the book. In particular, all R codes are discussed with enough detail to make them readily understandable and expandable.
Bibliography note	Includes bibliographical references (pages 287-290) and index.
Access restriction	Available only to authorized users.
Other forms	Also available online.
Technical details	Mode of access: World Wide Web
Issued in other form	Available online as: Marin, Jean-Michel. Bayesian essentials with R. Second edition. New York : Springer, 2014 9781461486879
Genre/form	Electronic books.
LCCN	2013950378
ISBN	9781461486862 (hbk)
ISBN	1461486866 (hbk)

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	Electronic Resources	Online Content Full text available from Springer Nature - Springer Mathematics and Statistics eBooks 2014 English International Full text available from Springer Nature - Springer Mathematics and Statistics eBooks 2014 English International	✔ Available

Bayesian essentials with R / Jean-Michel Marin, Christian P. Robert.

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