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Bayesian inference is a method of statistical inference that relies on treating the model parameters as random variables and applying Bayes' theorem to deduce subjective probability statements about the parameters or hypotheses, conditional on the observed dataset.

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, and if it is feasible, provide a simple example. [1.] James O. Berger, "Statistical Decision Theory and Bayesian Analysis" …
asked Jan 15 '18 by AlexMe
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2answers
I came across a question 8 at the end of chapter 3 of the book: "Give two simple examples showing a case in which a prior distribution would not be overwhelmed by data, regardless of the sample size …
asked Jan 13 '18 by AlexMe
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(\theta) \propto \frac{1}{θ(1−θ)}$$. Could anyone clarify which expression is the accurate one. 1. Approximation of improper priors 2. Bayesian Analysis of Some Common Distributions …
asked Jan 31 '18 by AlexMe
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Consider choosing $\theta^*$ that minimizes the expected absolute loss: \begin{align} \tag{1} \int_{\Theta}|\theta-\theta^*|\pi(\theta|\mathbf{x})d\theta= \int_{-\infty}^{\theta^*}(\theta^*-\theta)\p …
asked Nov 7 '18 by AlexMe