ISBN
| 9781461486862 |
DDC
| 519.542 |
Tác giả CN
| Marin, Jean-Michel, |
Nhan đề
| Bayesian essentials with R / Jean-Michel Marin, Christian P. Robert. |
Lần xuất bản
| Second edition. |
Thông tin xuất bản
| New York : Springer, 2014 |
Mô tả vật lý
| xiv, 296 pages :illustrations (some color) ; |
Tùng thư
| Springer Texts in Statistics, |
Tóm tắt
| 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. |
Thuật ngữ chủ đề
| R (Computer program language) |
Thuật ngữ chủ đề
| Bayesian statistical decision theory. |
Khoa
| Khoa Cơ bản |
Tác giả(bs) CN
| Robert, Christian P., |
|
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245 | 10|aBayesian essentials with R /|cJean-Michel Marin, Christian P. Robert. |
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250 | |aSecond edition. |
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260 | |aNew York : |bSpringer, |c2014 |
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300 | |axiv, 296 pages :|billustrations (some color) ; |
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490 | 1 |aSpringer Texts in Statistics, |
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504 | |aIncludes bibliographical references (pages 287-290) and index. |
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520 | |aThis 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. |
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541 | |aSpringer |
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650 | 0|aR (Computer program language) |
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650 | 0|aBayesian statistical decision theory. |
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690 | |aKhoa Cơ bản |
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700 | 1 |aRobert, Christian P.,|d1961-,|eauthor. |
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