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Choosing a multivariate normal framework for this analysis considerably simplifies the computations but this distribution has symmetric upper and lower tail dependence.
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Two distinct approaches are used the multivariate normal model and the chained equations approach.
The multivariate normal model was introduced by Rubin (1987; see also Little & Rubin 2002).
To begin with, the multivariate normal model has theoretical underpinnings whereas MICE does not.
In this paper, we reviewed two approaches to multiple imputation the multivariate normal model and the chained equations approach.
A multivariate normal model was assumed for.
This multivariate normal model fitted the data adequately.
This means the normal copula model is more robust than the multivariate normal model.
Multivariate normal mixture model clustering results of the Tamba area.
(a) Calculate a spatial density map of the previous earthquakes in the area using a multivariate normal mixture model.
Often a random dynamical system is considered as a complex Gaussian process and the framework of multivariate normal distributions is available to do a thorough formal analysis.
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