Sentence examples for by combining multivariate statistical from inspiring English sources

In recent years, predictive habitat distribution models, derived by combining multivariate statistical analyses with Geographic Information System (GIS) technology, have been recognised for their utility in conservation planning.

Promising methods therefore are cue-signal-response studies using partial least square regression (PLSR) methods which is a statistical procedure combining multivariate regression with parameter reduction.

1H NMR spectroscopy combined with multivariate statistical analysis showed classification of two vintages (2008 and 2009) of wines produced in Germany from different grape varieties, by different enological technologies and from different producing areas [55].

This study has demonstrated a promising potential of the custom-designed fluorescence imager combined with multivariate statistical tools in the study of beef meat.

The property integration framework is combined with multivariate statistical techniques and applied in a reverse problem formulation on chemical product design problems by systematic and insightful use of past data describing the properties of the raw materials, their blend ratios, and the process conditions during the production of a range of product grades to achieve new and improved products.

Since it involves a large quantity of data, it is often combined with multivariate statistical analysis in order to efficiently assess principal factors contributing to the phenotypic changes.

NMR spectroscopy fingerprinting, combined with multivariate statistical analysis, provides a powerful tool to detect metabolic changes induced by very low doses of EDs, allowing discrimination between several experimental groups on the basis of over- or underexpression of endogenous molecules.

By combining classical statistical methodology and cutting-edge machine learning algorithms (e.g.g

The Table provides the combined multivariate results.

Predefined risk factors and risk indicators were extracted from different national databases and combined in a multivariate statistical process control to obtain a risk assessment for each herd.

The volatile profiles of Pu-erh green teas from different mountains of origin (Jingmai and Wuliang) were evaluated by combining HS-SPME/GC-MS with multivariate statistical methods.