joint distribution

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joint distribution

[′jȯint ‚dis·trə¦byü·shən]
(statistics)
For two random variables Z and W, the distribution which gives the probability that Z = z and W = w for all values z and w of Z and W respectively.
References in periodicals archive ?
If X and Y are not independent of each other, linear or non-linear regression analysis is needed to determine joint probability density function.
An example of joint probability for educational background Gender Living place Educational Joint probability background Male Taipei NCU 0.
n], the joint probability for the BN is therefore obtained as follows:
Table 22 provides the joint probability of injury based on the response of the THOR-50M seated at mid-track in this study.
Bayes' posterior joint probability distribution is defined as the product of conditional distributions, and Gibbs sampling is said to work well in this case.
The full joint probability distribution for X is given as a product of local interactions by:
The joint probability distribution in G describes the given knowledge base, and Bayesian network expresses the knowledge model of a problem domain.
As discussed earlier, the simulations for the states are correlated: the joint probability distribution of the 51 election outcomes includes uncertainty about the national swing as well as state-by-state fluctuations.
In this paper we propose an extension of the standard single-feature mutual information similarity measure to a multi-feature mutual information measure, and solve the problem of efficient estimation of feature joint probability distribution in a high-dimensional feature space.
The Bayesian Joint Probability research was carried out through the Water Information Research and Development Alliance between CSIRO's Water for a Healthy Country Flagship and the Bureau.
In addition to clay content and LOI, the joint probability of inclusion (the joint probability of inclusion of 2 regressors X and Z is defined as the probability that at least 1 of the 2 coefficients is not zero) of all parent material dummies and soil horizon dummies was 95% and 100% (Table 2), respectively.
And the joint probability that the surplus immediately prior to ruin is smaller than x > 0 and the surplus after ruin is larger than -y with the initial surplus u as

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