Sentence examples for maximum variance and from inspiring English sources

The first axis defines the orientation of maximum variance and is proportional to the variance magnitude (λ1) defining an object length; secondary and tertiary axis are orthogonal and define in the same way width and height with associated sizes λ2 and λ3, respectively.

The shape model is trained employing Principal Components Analysis (PCA) on the aligned training shapes to find the eigenshapes of maximum variance and the mean shape s0.

Methods based on principal component analysis, which create orthogonal images along axes of maximum variance, and even Kubelka Munk-based models to remove the contributions from the final paint layer have been suggested [9, 16].

PCA, using the standard deviation as a criterion, implies that the components of the signal of interest in the data set have a maximum variance and the other components are mainly due to the noise.

We construct the spectral moment matrix (kappa _{ij}) and determine the eigenvalues (lambda _1) (maximum variance) and (lambda _2) (minimum variance) and the associated eigenvectors (vec {e}_1) and (vec {e}_2).

The mean, minimum, maximum, variance, and range in number of repeats across individuals were calculated from the repeat number dataset.

The PCs are mutually orthogonal and their extraction is such that the first PC holds the maximum variance, the second holds the second-maximum variance, and so on.

We used principle component method to analyze these eight items via maximum variance rotation, and to extract factors of general trust and particularized trust.

The expected KB(m) value was calculated on the basis of equation 12 described in Takahata et al. (1992), and its SE was estimated by maximum variance (Takahata and Tajima 1991).

The "maximum variance" method and the Minimum Circumscribed Circle/Ellipse formulations defined in the frequency domain are also discussed.

The new axes lie along the directions of maximum variance (Sarbu and Pop 2005).