Credal Set
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Credal Set

A credal set is a set of probability distributions[1] or, more generally, a set of (possibly finitely additive) probability measures. A credal set is often assumed or constructed to be a closed convex set. It is intended to express uncertainty or doubt about the probability model that should be used, or to convey the beliefs of a Bayesian agent about the possible states of the world.[2]

If a credal set ${\displaystyle K(X)}$ is closed and convex, then, by the Krein-Milman theorem, it can be equivalently described by its extreme points ${\displaystyle \mathrm {ext} [K(X)]}$. In that case, the expectation for a function ${\displaystyle f}$ of ${\displaystyle X}$ with respect to the credal set ${\displaystyle K(X)}$ forms a closed interval ${\displaystyle [{\underline {E}}[f],{\overline {E}}[f]]}$, whose lower bound is called the lower prevision of ${\displaystyle f}$, and whose upper bound is called the upper prevision of ${\displaystyle f}$:[3]

${\displaystyle {\underline {E}}[f]=\min _{\mu \in K(X)}\int f\,d\mu =\min _{\mu \in \mathrm {ext} [K(X)]}\int f\,d\mu }$

where ${\displaystyle \mu }$ denotes a probability measure, and with a similar expression for ${\displaystyle {\overline {E}}[f]}$ (just replace ${\displaystyle \min }$ by ${\displaystyle \max }$ in the above expression).

If ${\displaystyle X}$ is a categorical variable, then the credal set ${\displaystyle K(X)}$ can be considered as a set of probability mass functions over ${\displaystyle X}$.[4] If additionally ${\displaystyle K(X)}$ is also closed and convex, then the lower prevision of a function ${\displaystyle f}$ of ${\displaystyle X}$ can be simply evaluated as:

${\displaystyle {\underline {E}}[f]=\min _{p\in \mathrm {ext} [K(X)]}\sum _{x}f(x)p(x)}$

where ${\displaystyle p}$ denotes a probability mass function. It is easy to see that a credal set over a Boolean variable ${\displaystyle X}$ cannot have more than two extreme points (because the only closed convex sets in ${\displaystyle \mathbb {R} }$ are closed intervals), while credal sets over variables ${\displaystyle X}$ that can take three or more values can have any arbitrary number of extreme points.[]

## References

1. ^ Levi, I. (1980). The Enterprise of Knowledge. MIT Press, Cambridge, Massachusetts.
2. ^ Cozman, F. (1999). Theory of Sets of Probabilities (and related models) in a Nutshell Archived 2011-07-21 at the Wayback Machine.
3. ^ Walley, Peter (1991). Statistical Reasoning with Imprecise Probabilities. London: Chapman and Hall. ISBN 0-412-28660-2.
4. ^ Troffaes, Matthias C. M.; Gert, de Cooman (2014). Lower previsions. ISBN 9780470723777.

• Abellán, J. N.; Moral, S. N. (2005). "Upper entropy of credal sets. Applications to credal classification". International Journal of Approximate Reasoning. 39 (2-3): 235. doi:10.1016/j.ijar.2004.10.001.