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Varimax is so called because it maximizes the sum of the variances of the squared loadings (squared correlations between variables and factors). Preserving orthogonality requires that it is a rotation that leaves the sub-space invariant.
A varimax solution yields results which make it as easy as possible to identify each variable with a single factor. This is the most common orthogonal rotation option. [2] Quartimax rotation is an orthogonal rotation that maximizes the squared loadings for each variable rather than each factor.
To interpret the results, one proceeds either by post-multiplying the primary factor pattern matrix by the higher-order factor pattern matrices (Gorsuch, 1983) and perhaps applying a Varimax rotation to the result (Thompson, 1990) or by using a Schmid-Leiman solution (SLS, Schmid & Leiman, 1957, also known as Schmid-Leiman transformation) which ...
In mathematics, a rotation of axes in two dimensions is a mapping from an xy-Cartesian coordinate system to an x′y′-Cartesian coordinate system in which the origin is kept fixed and the x′ and y′ axes are obtained by rotating the x and y axes counterclockwise through an angle .
The case of θ = 0, φ ≠ 0 is called a simple rotation, with two unit eigenvalues forming an axis plane, and a two-dimensional rotation orthogonal to the axis plane. Otherwise, there is no axis plane. The case of θ = φ is called an isoclinic rotation, having eigenvalues e ±iθ repeated twice, so every vector is rotated through an angle θ.
Henry Felix Kaiser (June 7, 1927 – January 14, 1992) was an American psychologist and educator who worked in the fields of psychometrics and statistical psychology. He developed the Varimax rotation method and the Kaiser–Meyer–Olkin test for factor analysis in the late 1950s.
The Bellagio Gallery of Fine Art hosts rotating exhibits, so be sure to check the schedule online. I also suggest checking out Perception, a 17,000-square-foot digital-art museum.
In statistics and signal processing, the method of empirical orthogonal function (EOF) analysis is a decomposition of a signal or data set in terms of orthogonal basis functions which are determined from the data.