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In microeconomics, joint product pricing is the firm's problem of choosing prices for joint products, which are two or more products produced from the same process or operation, each considered to be of value. Pricing for joint products is more complex than pricing for a single product. To begin with, there are two demand curves.
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.
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).
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 ...
The mutual information of two multivariate normal distribution is a special case of the Kullback–Leibler divergence in which is the full dimensional multivariate distribution and is the product of the and dimensional marginal distributions and , such that + =.
The distribution of the product of correlated non-central normal samples was derived by Cui et al. [11] and takes the form of an infinite series of modified Bessel functions of the first kind. Moments of product of correlated central normal samples. For a central normal distribution N(0,1) the moments are
A model of the conditional distribution (=) is a model of the distribution of each label, and a model of the joint distribution is equivalent to a model of the distribution of label values (), together with the distribution of observations given a label, (); symbolically, (,) = ().
where the marginal, joint, and/or conditional probability density functions are denoted by ... (or, via the product topology, more) of the random variables.