Sentence examples for multidimensional scaling variable from inspiring English sources

The first dimension of the multidimensional scaling variable shows the best discrimination according to the proximities.

k-Means clustering using n variables acquired from multidimensional scaling of N dimensional variables in the matrix was performed to select representative conformers.

This technique was chosen over other ordination techniques because the data were nonlinear (cf principle components analysis), to avoid the arch effect produced when plotting the major axes of variation (cf correspondence analysis), and because of DCA's ability to utilise binary variables (cf multidimensional scaling) [ 9].

Multivariate data treatments (multiple regression models, variable ordination by multidimensional scaling, and discriminant analysis) were useful to identify the soil characteristics most significantly associated to its water repellency.

We used multiple correspondence analysis (MCA) to examine associations on variable level, and multidimensional scaling (MDS), k-means and fuzzy cluster analyses to search for subgroups on patient level.

There was a clear distinction in the naïve CD4+ T cell DNA methylation profile between African-Americans and European-Americans as demonstrated in a multidimensional scaling plot of the 1000 most variable array probes after batch effect adjustment (Fig.  1).

Next, we performed multidimensional scaling of the top 1% most variable CpGs to assess the inter-sample variability within each dataset.

To identify environmental factors that may be related to community differentiation, we projected vectors of edaphic variables onto nonmetric multidimensional scaling (NMDS) ordinations of community dissimilarity measures.

Results from non-parametric multidimensional scaling and regression analyses indicate that variables relating to both the environmental and social ecology of humans and birds in Vietnam interact to affect the genetic character of viruses.

The summed data matrixes also were evaluated following multidimensional scaling to detect additional relationships between variables.

From the 950 initial metabolic variables extracted from spectra, the multidimensional scaling procedure was repeatedly applied to select 395 fully informative metabolic variables, to which were applied an orthogonal signal correction procedure based on a partial least squares (PLS) regression using dummy variables designed according to the "time" and "cultivar" effects.