Sentence examples for multivariate data is from inspiring English sources

A possible extension to multivariate data is briefly indicated.

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.

In this paper, an innovative method based on Kullback-Leibler divergence for detecting incipient anomalies in highly correlated multivariate data is presented.

However, one issue that arises with this correlated multivariate data is the number of zero counts increases as crash counts have many categories.

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

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.

Multivariate data were collected for a mean of 67 ± 48 hours.

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