maximum entropy probability distribution造句

This general result of the Gibbs algorithm is then a maximum entropy probability distribution.
Every probability distribution is trivially a maximum entropy probability distribution under the constraint that the distribution have its own entropy.
The log-normal distribution is the maximum entropy probability distribution for a random variate X for which the mean and variance of \ ln ( X ) are specified.
It is the maximum entropy probability distribution for a random variate " X " under no constraint other than that it is contained in the distribution's support.
In statistics and information theory, a "'maximum entropy probability distribution "'has entropy that is at least as great as that of all other members of a specified class of probability distributions.
It's difficult to find maximum entropy probability distribution in a sentence. 用maximum entropy probability distribution造句挺难的

Finally, the normal distribution saturates the inequality, and it is the only distribution with this property, because it is the maximum entropy probability distribution among those with fixed variance ( cf . here for proof ).