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Bayesian Inference

  1. Oct 28, 2007 #1
    I am reading a topic on Bayesian Inference.I read books from different authors but they are all the same. I cannot see how the terms are derived.

    Could anyone briefly explain what is going on and what is it that we are trying to find using this Bayesian. Bayesian is a combination of belief from past data. So Im thinking that we are making the prediction. But Im not sure of what sort of prediction. Is ther an example to this.

    I need help in understanding the 1) Bayesian formalism and
    2) the mean of a gaussian distribution - how are the parameters; mu and the variance are derived and how is the posterior distri bution derived as well.

    By the way could anyone suggest any recommended books for this topic. Thx
    Last edited: Oct 28, 2007
  2. jcsd
  3. Oct 28, 2007 #2

    Chris Hillman

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    Kapur and Kesevan.
  4. Oct 28, 2007 #3


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    In practice Bayesian inference comes down to a weighting of prior beliefs vs. actual observations. I.e. the posterior mean is a weighted average of the prior beliefs (e.g. [itex]\mu_0[/itex]) and the data average.
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