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in October issue.) ANALYSIS OF A COMPLEX OF STATISTICAL VARIABLES INTO PRINCIPAL COMPONENTS1 HAROLD HOTELLING Columbia University 1. INTRODUCTION Consider n variables attaching to each individual ...
equations––convergence; tests as samples of a larger aggregate of tests; principal components with perfect weighting; and the "sand" and "cobblestone" theories of the mind. ANALYSIS OF A COMPLEX ...
FOOTNOTES 1 . H. H. Harman, Modern Factor Analysis , 2d ed. rev. (Chicago: University of Chicago Press, 1967), p. 4. 2 . . H. Hotelling , “ Analysis of a Complex of Statistical Variables ...
," a critique of Hotelling's method of " Analysis of a Complex of Statistical Variables into Principal Components," published in the September and October issues of The Journal of Educational Psychology for 1933 ...
seminal 20th century work on the ‘ analysis of a complex of statistical variables into principal components’ [2]. About five decades later, PCA found its way into regression analysis to summarize large ...
of exploratory use of real principal component analysis (RPCA) to complex data tables clears the deficiency existing in complex principal component analysis (CPCA), a method mainly developed in the statistical ...
. This model introduces additional discrete latent variables to the original structure. The Bayesian nonparametric nature of this new model allows it to adapt complexity as more data is observed and project each ...
Abstract: Dimensionality reduction on Riemannian manifolds is challenging due to the complex nonlinear data structures. While probabilistic principal geodesic analysis ~(PPGA) has been proposed ...
Complex analyses involving multiple, dependent random quantities often lead to graphical models—a set of nodes denoting variables of interest, and corresponding edges denoting statistical ...
Complex principal component analysis (CPCA) is a linear multivariate technique commonly applied to complex variables or 2‐dimensional vector fields such as winds or currents. A new nonlinear CPCA ...
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