Sentence examples for approaches and multivariate from inspiring English sources

These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers.

All these tests can be performed under different assumptions and with slightly different approaches, and multivariate analyses are generally performed.

Both the empirical approach and multivariate statistical techniques, including principal components analysis (PCA), and linear discriminant analysis (LDA), together with the leave-one-sample-out cross-validation method, were employed to develop effective diagnostic algorithms for classification of Raman spectra between normal and dysplastic gastric tissues.

In standard clinical epidemiological approaches, univariate and multivariate regression analyses are performed to determine significant and independent predictors of disease development.

It is recommended that future studies should use valid instruments, apply sound methodological approaches and adequate multivariate statistical analyses adjusted for socio-demographic characteristics and known clinical prognostic factors with a satisfactory validation strategy.

In analyses using this approach, univariate and multivariate logistic regression analyses confirmed that densities of CD3+, CD8+, and CD45RO+ TILs were independent predictors of regional lymph node metastasis (Table 7).

RTR specification with mathematical model and different approaches to multivariate statistical process control supporting process analytical technologies are also presented.

In this chapter, we introduce the basics of SPC, providing an overview of different approaches for univariate and multivariate processes.

There are two main approaches of univariate and multivariate analyses in forecasting financial time series where ANNs can be used in both (Cao and Tay 2001).

Two types of data analysis approaches, univariate analysis and multivariate analysis, have been widely used in metabolomics projects, including most of the CF related studies referenced in this paper.

Given its novel multivariate testing of functional SNPs, JEPEG is a complementary tool to the commonly used univariate GWAS approach and agnostic multivariate approaches like VEGAS.