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    Bayesian Methods for Statistical Analysis

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    https://library.oapen.org/bitstream/20.500.12657/32424/1/611011.pdf
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    https://library.oapen.org/bitstream/20.500.12657/32424/1/611011.pdf
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    https://library.oapen.org/bitstream/20.500.12657/32424/1/611011.pdf
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    https://library.oapen.org/bitstream/20.500.12657/32424/1/611011.pdf
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    https://library.oapen.org/bitstream/20.500.12657/32424/1/611011.pdf
    Author(s)
    Puza, Borek
    Language
    English
    Show full item record
    Abstract
    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.
    URI
    https://directory.doabooks.org/handle/20.500.12854/32870
    Keywords
    statistics; mathematics; bayesian inference; probability; Algorithm; Confidence interval; Histogram; Monte Carlo method; Posterior probability; Sampling (statistics); WinBUGS; thema EDItEUR::P Mathematics and Science::PB Mathematics; thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics; thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference
    DOI
    10.26530/OAPEN_611011
    ISBN
    9781921934254
    Publisher
    ANU Press
    Publisher website
    http://press.anu.edu.au
    Publication date and place
    2015
    Rights
    http://press.anu.edu.au/about/conditions-use
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    Credits


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      This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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