bivariate distribution

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bivariate distribution

[bī¦ver·ē·ət ‚dis·trə′byü·shən]
(statistics)
The joint distribution of a pair of variates for continuous or discontinuous data.
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References in periodicals archive ?
For the Gaussian copula, it is to be noted that with Gaussian marginals, it in effect results in a multivariate normal distribution, that is, we have
Among their topics are matrix algebra, the multivariate normal distribution, tests on covariance matrices, principle component analysis, cluster analysis, and graphical procedures.
For multivariate normal distribution, we organized the data into an n X p matrix, X, where the p columns were measurements and calculated values, and the n row vectors were the 3 attributes: [log.
A multivariate normal distribution for the data is an important assumption in SEM analyses such as CFA.
The prior distribution of [mu] is chosen to be a conjugated multivariate normal distribution [N.
In MI, the variables are assumed to have a joint multivariate normal distribution (Allison, 2002).
20 Distribution of the Sample Multiple Correlation Coefficient From Multivariate Normal Distribution
A multivariate normal distribution was assumed for K and statistical techniques were used as well as expert opinion to develop likely "low" and "high" values for each variable in K.
If the forecast error has a multivariate normal distribution with mean 0 and variance [OMEGA], then the analog of (1) is
The fundamental assumption underlying all MRA is that the data used to fir the regression model form a multivariate normal distribution.
Whether or not stock returns conform to a multivariate normal distribution is an issue of general importance to researchers in finance.
We make the formal assumption that the sherds analysed from Ur comprise an independent random sample drawn from a reference population in which the composition vector has a multivariate normal distribution.

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