Bayesian statistics : an introduction /
Among statisticians the Bayesian approach continues to gain adherents and this new edition of Peter Lee's classic introduction maintains the clarity of exposition and use of examples for which the text is known and praised. In addition, there is extended coverage of the Metropolis-Hastings algo...
Disimpan dalam:
| Pengarang Utama: | |
|---|---|
| Format: | Buku |
| Bahasa: | English |
| Diterbitkan: |
London ; New York :
Arnold,
c2004.
|
| Edisi: | 3rd ed. |
| Subjek-subjek: | |
| Penanda-penanda: |
Tambah Penanda
Tiada Penanda, Jadilah orang pertama menanda rekod ini!
|
| LEADER | 01711cam a2200301 a 4500 | ||
|---|---|---|---|
| 001 | 009411054-9 | ||
| 005 | 20040802122920.0 | ||
| 008 | 040405s2004 enka b 001 0 eng d | ||
| 015 | |a GBA4-Z6482 | ||
| 020 | |a 0340814055 (pbk.) | ||
| 035 | 0 | |a ocm54888001 | |
| 040 | |a CPV |c CPV |d OCLCQ |d UKM | ||
| 050 | 0 | 0 | |a QA279.5 |b .L44 2004 |
| 082 | 0 | 4 | |a 519.542 |2 21 |
| 090 | |a QA279.5 |b .L44 2004 | ||
| 100 | 1 | |a Lee, Peter M. | |
| 245 | 1 | 0 | |a Bayesian statistics : |b an introduction / |c Peter M. Lee. |
| 250 | |a 3rd ed. | ||
| 260 | |a London ; |a New York : |b Arnold, |c c2004. | ||
| 300 | |a xv, 351 p. : |b ill. ; |c 23 cm. | ||
| 504 | |a Includes bibliographical references (p. [337]-346) and index. | ||
| 505 | 0 | 0 | |g 1. |t Preliminaries -- |g 2. |t Bayesian inference for the normal distribution -- |g 3. |t Some other common distributions -- |g 4. |t Hypothesis testing -- |g 5. |t Two-sample problems -- |g 6. |t Correlation, regression and the analysis of variance -- |g 7. |t Other topics -- |g 8. |t Hierarchical models -- |g 9. |t Gibbs sampler and other numerical methods. |
| 520 | |a Among statisticians the Bayesian approach continues to gain adherents and this new edition of Peter Lee's classic introduction maintains the clarity of exposition and use of examples for which the text is known and praised. In addition, there is extended coverage of the Metropolis-Hastings algorithm as well as an introduction to the use of BUGS, as this is now the standard computational tool for such numerical work. Other alterations include new material on generalized linear modeling and Bernardo's theory of reference points. | ||
| 650 | 0 | |a Bayesian statistical decision theory. | |
| 650 | 2 | |a Bayes Theorem. | |
| 899 | |a 415_565869 | ||
| 988 | |a 20040716 | ||
| 906 | |0 OCLC | ||