enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Joint probability distribution - Wikipedia

    en.wikipedia.org/wiki/Joint_probability_distribution

    The joint distribution encodes the marginal distributions, i.e. the distributions of each of the individual random variables and the conditional probability distributions, which deal with how the outputs of one random variable are distributed when given information on the outputs of the other random variable(s).

  3. Marginal distribution - Wikipedia

    en.wikipedia.org/wiki/Marginal_distribution

    Joint and marginal distributions of a pair of discrete random variables, X and Y, dependent, thus having nonzero mutual information I(X; Y). The values of the joint distribution are in the 3×4 rectangle; the values of the marginal distributions are along the right and bottom margins.

  4. Conditional mutual information - Wikipedia

    en.wikipedia.org/wiki/Conditional_mutual_information

    where the marginal, joint, and/or conditional probability density functions are denoted by with the appropriate subscript. This can be simplified as

  5. Mutual information - Wikipedia

    en.wikipedia.org/wiki/Mutual_information

    The joint information is equal to the mutual information plus the sum of all the marginal information (negative of the marginal entropies) for each particle coordinate. Boltzmann's assumption amounts to ignoring the mutual information in the calculation of entropy, which yields the thermodynamic entropy (divided by the Boltzmann constant).

  6. Conditional probability distribution - Wikipedia

    en.wikipedia.org/wiki/Conditional_probability...

    The conditional distribution contrasts with the marginal distribution of a random variable, which is its distribution without reference to the value of the other variable. If the conditional distribution of Y {\displaystyle Y} given X {\displaystyle X} is a continuous distribution , then its probability density function is known as the ...

  7. What Is the Marginal vs. Effective Tax Rate? - AOL

    www.aol.com/finance/marginal-vs-effective-tax...

    Wage earners can employ a similar strategy by asking their employer to hold year-end bonuses until January. Take all available credits and deductions. Maximize contributions to pre-tax retirement ...

  8. Gibbs sampling - Wikipedia

    en.wikipedia.org/wiki/Gibbs_sampling

    Gibbs sampling is named after the physicist Josiah Willard Gibbs, in reference to an analogy between the sampling algorithm and statistical physics.The algorithm was described by brothers Stuart and Donald Geman in 1984, some eight decades after the death of Gibbs, [1] and became popularized in the statistics community for calculating marginal probability distribution, especially the posterior ...

  9. Tax expert: Here's why some married couples should file ... - AOL

    www.aol.com/finance/tax-expert-heres-why-married...

    In many cases, it's better for married couples to file jointly because they cannot claim tax credits, like education credits and credits related to child care, if they file married filing separately.