Sentence examples for multivariate distribution model from inspiring English sources
To overcome this, we propose using a multivariate distribution model of distinct tensor components to characterise the variability of stress tensors referred to a common Cartesian coordinate system.
A recent trend of geotechnical correlation analysis is to construct a multivariate distribution model to describe the multiple dependency characteristics of different soil parameters.
Finally, actual in situ stress results are used to confirm the multivariate characteristics of stress data and the derived properties of the proposed multivariate distribution model, as well as to demonstrate how the quasi-tensorial approach may give biased results.
Besides, the Johnson system of distribution is superior to the Box-Cox transformation in the construction of the multivariate distribution model in the sense that the former is more effective to achieve the standard normal distribution, especially for the soil parameters with a bounded distribution.
We consider new plausible distribution candidates to tackle the multivariate distribution modeling challenges.
In recent studies, Gazor et al. [14] and Jensen et al. [21] have used the moment test and have shown that Laplace multivariate distribution models speech signal or its representations are better than the Gaussian multivariate distribution.
Multivariate Gaussian distribution model is the only model for which the above-mentioned decomposition is analytically available (Deutsch 2002).
A smooth multivariate wind distribution model is developed to capture the coupled variation of wind speed, wind direction, and air density.
Thus, a cost model combining Costa's cost model with the multivariate normal distribution model given by Yang and Hancock is developed in this study to explore the effect of correlation on the designed chart parameters.
When multiple markers are continuous and normally distributed, Fisher's LDA provides the best linear combination that maximizes the sensitivity over the entire specificity range uniformly under the multivariate normal distribution model [ 11].
The multivariate distribution is used to model one variable for multiple tips on a tree, rather than to model multiple characters.
