Sentence examples for multivariate analysis methods from inspiring English sources
Introduction to statistical multivariate analysis methods and their applications to analyze data and mathematical models.
Multivariate analysis methods, such as Clustering analysis and Principle component analysis, were applied to determine the quality differences between samples.
A methodology based on Fourier transform infrared (FTIR) spectroscopy, combined with multivariate analysis methods, was applied in order to monitor extra virgin olive oils produced from three distinct cultivars on different maturation stages.
Soft-modeling and multivariate analysis methods have been shown to be very powerful for the analysis of electrochemical data, especially for multianalyte calibration and modeling in multicomponent dynamic systems.
The use of multivariate analysis methods, together with electronic senses, has shown to be very powerful; however, due to the high complexity of food, the employment of just single sensor data is often insufficient.
The instrument was controlled by a microcomputer and was designed to perform absorbance measurements in a single wavelength continuously as well as in all wavelengths (470, 500, 562, 590, 612, 636 and 654 nm) sequentially, allowing its application in multivariate analysis methods.
We performed double-trait genome scans using our recently developed multivariate analysis method implemented in the MultiABEL package9.
Similarly, applying a multivariate analysis method (linear support vector machines, SVM) to probe the orientation specific BOLD signal instead did not yield any significant effects of attention and expectation in any of the ROIs.
Furthermore, the conversion was tracked quantitatively with both spectroscopic methods using the multivariate analysis method, partial least squares regression.
The objective of the current research is to establish a predictive model of DLC properties using a multivariate analysis method.
A relatively new multivariate analysis method called Co-plot is shown to be highly efficient for the geometrical representation of multicriteria decision problems.
