Sentence examples for data with eigenvalues from inspiring English sources

Principal components model was used to summarise the data with eigenvalues greater than 1.

One component was found for the Swedish, Norwegian national and for the Faroese data with eigenvalues of 3.82, 3.68 and 3.62, respectively.

In the example we measured the sample eigenvalues of synthetic data, with the population eigenvalues uniformly distributed between 1 and 3. To show that the (GSA) limit 'if p → ∞' is relevant we set p to 6,20, and 100, while keeping γ = 1 3, so N = 18,60, and 300, respectively.

To test this in the Taiwan data, two factors with eigenvalues greater than 1 were extracted, which accounted for 60% of the total variance in SF-36 scale scores.

The decision rule is to compare the eigenvalues from the data with the randomly calculated eigenvalues, retaining as factors, all factors where the former is larger than the latter.

Generally, Rasch-conforming data produces residual-factors with eigenvalues up to 2.0 [ 43].

Results of PCA and measures of internal consistency are shown in table 3. The Finnish data gave two components, with eigenvalues of 3.38 and 1.02.

Since the eigenvalue of a principal components < 1 implies that from total variance the variance accounted by a component is less than one, the principal component with large eigenvalue were chosen to explain the variation in the data set (usually with eigenvalue > 1).

Table 8 shows that test-one data results in six components with eigenvalues greater than one.

Dividing data by back pain experience did not result in convergence, whereas dividing data by gender indicated 11 components with eigenvalues ≥1.

The novel aspect is the combination of the general technical principle of projection pursuit for multivariate data with the neutron multiplication eigenvalue problem in the nuclear engineering discipline.