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It is well known that if Ω ∈ L log L(Sn-1), h = 1, by the method of rotations, Calderón and Zygmund [1] proved that S extends to a bounded operator on L p for all p ∈ (1, ∞).
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Correlation coefficients revisited The correlation matrix and PCA The component matrix The rotated component matrix A detailed example Choosing a method of rotation Sample size requirements Hierarchical multiple factor analysis The effects of variable selection.
In this paper, the gas action effect has been analyzed by the method of rotation vector decomposition.
Impervious area data were derived from the Landsat images using superior ensemble learning method of rotation forest.
Finally, this inconsistency could be ascribed to different analytical methods to examine the FLCAS a different type of exploratory factor analysis with a different method of rotation.
Thus, for the sake of brevity in interpretation, this study used varimax method of rotation variables that helps to reduce the number of variables with a high loading on a factor.
In [18], Chen proved that T is bounded on L p (ℝ n × ℝ m ) for 1 < p < ∞ when Ω ∈ L log L 2 (Sn-1× Sm-1) and h = 1 where he mainly relies on the method of rotation.
Construct validity was analysed by "the maximum-likelihood method" and "direct oblimin method" of rotation (factor analysis).
Factor loading score of ≥40% and varimax method of rotation was considered to load items on confirmed or identified subdimension scales.
Finally, there are limitations inherent to principal component analysis owing to arbitrary decisions in determining the number of factors to retain, in choosing the method of rotation of the initial factors, and in labeling the dietary patterns (9, 21).
The use of factor analysis requires some arbitrary decision-making regarding the assignment of foods to food groups, the number of retained factors, the method of rotation, and the labels of components [ 44].
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