October 2015
Beginner to intermediate
168 pages
4h 11m
English
Content preview from Learning Bayesian Models with R
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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:
Or:
Note that marginal distribution is very different from conditional distribution. In conditional ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.