I am doing some reading and am seeing phrases such as the following. For context, I am learning about Bayes Inference and prior/posterior distributions so theta is the parameter:
In such problems, we shall refer to the distribution indexed by θ for the other random variables of interest as the conditional distribution for those random variables given θ.
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In many problems, such as Example 7.2.1, the observable data X1, X2, . . . are modeled as a random sample from a univariate distribution indexed by θ.
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In these cases, let f (x|θ) denote the p.f. or p.d.f. of a single random variable under the distribution indexed by θ.
What does "indexed" mean and how do I conceptualize it?
