Sentence examples for multivariate data are from inspiring English sources

In crash frequency studies, correlated multivariate data are often obtained for each roadway entity longitudinally.

Here, outlier detection methods in low and high dimension, as well as important robust estimators and methods for multivariate data are reviewed, and the most important references to the corresponding literature are provided.

Another popular way to display multivariate data are glyph or icon displays.

The well-known methods for handling multivariate data are related to dimension reduction, clustering, classification, and regression.

All multivariate data are presented as rate ratios, which give the ratio of the mean values for GAD patients versus non-GAD controls.

After selecting the threshold, all entities of the multivariate data are considered as the nodes of a network and an edge is inserted between the pair of entities for which the similarity is more than the threshold.

A possible extension to multivariate data is briefly indicated.

The normality of multivariate data was tested using probability plot of PCA model.

The analysis of such multivariate data is usually based on MANOVA models assuming multivariate normality and covariance homogeneity.

The detection of outliers in multivariate data is one of the most important problems in the physical, chemical, medical and engineering sciences.

This type of dependent multivariate data is characterized by positive components which sum to one, and occurs in several applications in science and engineering.