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January 11th, 2017, 08:52 AM   #1
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Maximal entropy distribution

What is the maximal entropy distribution for a positive random variable for which we know the first and second moment?

$\displaystyle X>0$

$\displaystyle E[X]=a$

$\displaystyle E[X^2]=4a^2$
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January 11th, 2017, 10:15 AM   #2
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I have no idea, but this site might help:

https://en.wikipedia.org/wiki/Maximu...y_distribution

Discrete version
Suppose $\displaystyle S = \{x_1,x_2,...\}$ is a (finite or infinite) discrete subset of the reals and we choose to specify n functions $\displaystyle f_1,...,f_n$ and n numbers $\displaystyle a_1,...,a_n$. We consider the class C of all discrete random variables X which are supported on S and which satisfy the n conditions

$\displaystyle {\displaystyle \operatorname {E} (f_{j}(X))=a_{j}\quad {\mbox{ for }}j=1,\ldots ,n} $

If there exists a member of C which assigns positive probability to all members of S and if there exists a maximum entropy distribution for C, then this distribution has the following shape:

$\displaystyle {\displaystyle \operatorname {Pr} (X=x_{k})=c\exp \left(\sum _{j=1}^{n}\lambda _{j}f_{j}(x_{k})\right)\quad {\mbox{ for }}k=1,2,\ldots }$

where the constants c and λj have to be determined so that the sum of the probabilities is 1 and the above conditions for the expected values are satisfied. Conversely, if constants c and λj like this can be found, then the above distribution is indeed the maximum entropy distribution for our class C.
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