| 000 | 02446nam a22003738i 4500 | ||
|---|---|---|---|
| 001 | CR9781108646185 | ||
| 003 | UkCbUP | ||
| 005 | 20200124160157.0 | ||
| 006 | m|||||o||d|||||||| | ||
| 007 | cr|||||||||||| | ||
| 008 | 180614s2019||||enk o ||1 0|eng|d | ||
| 020 | _a9781108646185 (ebook) | ||
| 020 | _z9781108481038 (hardback) | ||
| 020 | _z9781108703741 (paperback) | ||
| 040 |
_aUkCbUP _beng _erda _cUkCbUP |
||
| 050 | 0 | 0 |
_aQA279.5 _b.T87 2019 |
| 082 | 0 | 4 |
_a519.542 _223 |
| 100 | 1 |
_aTurkman, Maria Antónia Amaral, _d1949- _eauthor. |
|
| 245 | 1 | 0 |
_aComputational Bayesian statistics : _ban introduction / _cM. Antónia Amaral Turkman, Carlos Daniel Paulino, Peter Müller. |
| 264 | 1 |
_aCambridge : _bCambridge University Press, _c2019. |
|
| 300 |
_a1 online resource (xi, 243 pages) : _bdigital, PDF file(s). |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
||
| 490 | 1 |
_aInstitute of Mathematical Statistics textbooks ; _v11 |
|
| 500 | _aTitle from publisher's bibliographic system (viewed on 20 Feb 2019). | ||
| 520 | _aMeaningful use of advanced Bayesian methods requires a good understanding of the fundamentals. This engaging book explains the ideas that underpin the construction and analysis of Bayesian models, with particular focus on computational methods and schemes. The unique features of the text are the extensive discussion of available software packages combined with a brief but complete and mathematically rigorous introduction to Bayesian inference. The text introduces Monte Carlo methods, Markov chain Monte Carlo methods, and Bayesian software, with additional material on model validation and comparison, transdimensional MCMC, and conditionally Gaussian models. The inclusion of problems makes the book suitable as a textbook for a first graduate-level course in Bayesian computation with a focus on Monte Carlo methods. The extensive discussion of Bayesian software - R/R-INLA, OpenBUGS, JAGS, STAN, and BayesX - makes it useful also for researchers and graduate students from beyond statistics. | ||
| 650 | 0 |
_aBayesian statistical decision theory _vTextbooks. |
|
| 700 | 1 |
_aPaulino, Carlos Daniel, _eauthor. |
|
| 700 | 1 |
_aMüller, Peter, _d1963 August 9- _eauthor. |
|
| 776 | 0 | 8 |
_iPrint version: _z9781108481038 |
| 830 | 0 |
_aInstitute of Mathematical Statistics textbooks ; _v11. |
|
| 856 | 4 | 0 | _uhttps://doi.org/10.1017/9781108646185 |
| 999 |
_c514520 _d514518 |
||