As stated by Sklar (1959), copula couples the multivariate distribution to its marginal distributions which are uniformly distributed on [0,1].
Therefore, any multivariate distribution is applicable.
Copula is a function with multivariate distribution.
First, the multivariate distribution of the asset returns is fitted by a multivariate distribution.
In this paper, we investigate multivariate distribution of speech signal in the time and transformed domains.
The whole study of multivariate distribution in this paper is concentrated on clean speech signals.
As the COP approach has no closed-form solution, simulations from this multivariate distribution are necessary.
In general, speech processing algorithms using multivariate distribution exploit different feature types to process speech signals.
We consider new plausible distribution candidates to tackle the multivariate distribution modeling challenges.
In other words, the multivariate distribution is coupled to its marginal distributions.
Therefore, the distribution of market returns is fitted by a multivariate distribution.
