Abstract
Bayesian statistics is based up a philosophy different from that of other methods of statistical inference. In Bayesian statistics all unknowns, and in particular unknown parameters, are considered to be random variables and their probability distributions specify our beliefs about their likely values. Estimation, model selection, and uncertainty analysis are implemented by using Bayes's theorem to update our beliefs as new data are observed.
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© 2011 Springer Science+Business Media, LLC
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Ruppert, D. (2011). Bayesian Data Analysis and MCMC. In: Statistics and Data Analysis for Financial Engineering. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7787-8_20
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DOI: https://doi.org/10.1007/978-1-4419-7787-8_20
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