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Learning Bayesian Models with R by Dr. Hari M. Koduvely

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Marginal distribution

In many situations, we are interested only in the probability distribution of a subset of random variables. For example, in the heart disease problem mentioned in the previous section, if we want to infer the probability of people in a population having a heart disease as a function of their age only, we need to integrate out the effect of other random variables such as blood pressure and diabetes. This is called marginalization:

Marginal distribution

Or:

Marginal distribution

Note that marginal distribution is very different from conditional distribution. In conditional ...

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