Sentence examples for maximal variance of from inspiring English sources

A design is said to be A-optimal in such situations if it minimizes the sum of the variances of the least-squares estimates for the elementary treatment contrasts between the test treatments and the standard treatments and a design is said to be MV-optimal if it minimizes the maximal variance of the same least squares estimates.

The direction of maximal variance of PC1 correlates strongly with OA disease state.

A maximal variance of 2*10-4 2*10-4und showasg that changing the root prior does not infoundce age eshowings.

PCA in nutritional analyses aims to account for the maximal variance of dietary intake by combining the many different dietary variables into a smaller number of factors based on the intercorrelation of these variables.

First, bivariate curve adaptations were calculated using linear, quadratic, cubic, inverse, composite (inverse and polynom together), exponential, logarithmic, logistic, and s-shaped function characteristics of the dependent variable to find the optimal curve adaptation for each single cofactor explaining maximal variance of the dependent strength variable.

For each choice of s1 and s2, the maximal variance over values of s 1 f and s 2 f is given by Equation 57.

The focus of their work is on consistency in terms of estimating the true direction of maximal variance which corresponds to consistency in the parameter estimation of a statistical model.

Typically, the PCs are uncorrelated, i.e. the first PC points in the direction of maximal variance and the second PC shows in the direction of maximal variance orthogonal to the first PC and so on.

DAPC first centers and scales genetic data and performs a principal component analysis from which the axes of maximal variance are extracted.

Differently to PCA where the data are projected on the directions of maximal variance, in Laplacian-eigenmaps the first eigenvectors entail the direction preserving the distance among the examples.

They showed that under the assumption that the true loadings vector is sparse and given that the underlying signal is strong relative to the number of variables involved, sparse PCA methods are able to consistently estimate the direction of maximal variance.