| id |
oapen-20.500.12657-32424
|
| record_format |
dspace
|
| spelling |
oapen-20.500.12657-324242022-04-26T12:25:57Z Bayesian Methods for Statistical Analysis Puza, Borek statistics mathematics bayesian inference probability Algorithm Confidence interval Histogram Monte Carlo method Posterior probability Sampling (statistics) WinBUGS bic Book Industry Communication::P Mathematics & science::PB Mathematics bic Book Industry Communication::P Mathematics & science::PB Mathematics::PBT Probability & statistics bic Book Industry Communication::P Mathematics & science::PB Mathematics::PBT Probability & statistics::PBTB Bayesian inference Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse. The book contains many exercises, all with worked solutions, including complete computer code. It is suitable for self-study or a semester-long course, with three hours of lectures and one tutorial per week for 13 weeks. 2016-06-23 00:00:00 2020-04-01T14:10:01Z 2020-04-01T14:10:01Z 2015 book 611011 OCN: 1076716258 9781921934254 http://library.oapen.org/handle/20.500.12657/32424 eng application/pdf n/a 611011.pdf http://press.anu.edu.au/publications/bayesian-methods-statistical-analysis ANU Press 10.26530/OAPEN_611011 10.26530/OAPEN_611011 ddc8cc3f-dd57-40ef-b8d5-06f839686b71 9781921934254 open access
|
| institution |
OAPEN
|
| collection |
DSpace
|
| language |
English
|
| description |
Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse. The book contains many exercises, all with worked solutions, including complete computer code. It is suitable for self-study or a semester-long course, with three hours of lectures and one tutorial per week for 13 weeks.
|
| title |
611011.pdf
|
| spellingShingle |
611011.pdf
|
| title_short |
611011.pdf
|
| title_full |
611011.pdf
|
| title_fullStr |
611011.pdf
|
| title_full_unstemmed |
611011.pdf
|
| title_sort |
611011.pdf
|
| publisher |
ANU Press
|
| publishDate |
2016
|
| url |
http://press.anu.edu.au/publications/bayesian-methods-statistical-analysis
|
| _version_ |
1771297510472548352
|
