Sentence examples for multivariate discriminant function from inspiring English sources

Hence, a multivariate discriminant function analysis was conducted to determine which parameters discriminate between diabetic patients without microvascular diseases and those suffering from neuropathy, peripheral neuropathy or retinopathy.

Ranks were derived from a multivariate discriminant function analysis based on results from the goodness of fit tests [19].

We then analyzed the partial warps and uniform scores using a multivariate discriminant function analysis (DFA) based on the classification of individuals into the different spawning depths.

The multivariate discriminant function analysis tool (©Statistica 10.0, StatSoft, Germany) was used to determine which variables discriminate between healthy and sick persons for the three important complications: nephropathy, peripheral neuropathy, and retinopathy.

We used separate conical variate analyses (CVA; JMP 5.1.1 statistical software) for each dataset, which generates a classification matrix of group membership, with individual posterior probabilities, based on multivariate discriminant functions.

Through the use of statistical methods (multivariate analysis, discriminant function analysis, neural analysis) and through the study of minarets' dimensions, we have obtained important relations and proportions from an archaeological point of view and within the context of the architecture of the old Islamic minarets in Al-Andalus.

SVM-RFE is also shown to be more effective than wrapper methods using RFE and other multivariate linear discriminant functions, such as linear discriminant analysis and mean-squared error (Pseudo-inverse) (Guyon et al., 2002).

To reveal the significance of those variables that describe the circle of the curve (RD and RS) in group classification a multivariate exploratory technique, discriminant function analysis was used with p <0.05 level.

Mineralogical (X-ray diffraction) and geochemical (X-ray fluorescence) compositional data of Alpine Tethyde mudrocks from Sicily were used to unravel the interplay of provenance and diagenesis by means of multivariate statistical methods (PCA, discriminant function analysis) designed for non-negative constant-sum data.

Multivariate analysis of variance and discriminant function analysis are applied for data processing.

In a last step, we used multivariate methods (i.e. discriminant function analyses) to demonstrate statistically if and how distinctiveness of individuals changes with hunger.