Results 61 to 70 of about 194,565 (112)
Sudden unexpected death in infancy:A statistical analysis of certain socioeconomic factors
, 1968 Marie Valdés-Dapena +4 more
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A NEW PROPOSITION ON NUMBER OF FACTORS AND COMMUNALITIES IN MULTIPLE-FACTOR ANALYSIS
, 1964 Shigeo Kashiwagi
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A NEW OBJECTIVE PROCEDURE FOR THE ORTHOGONAL ROTATION IN FACTOR ANALYSIS (1)
, 1963 Shigeo Kashiwagi
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Factor analysis regression [PDF]
Statistical Papers, 2006 In the presence of multicollinearity the literature points to principal component regression (PCR) as an estimation method for the regression coefficients of a multiple regression model. Due to ambiguities in the interpretation, involved by the orthogonal transformation of the set of explanatory variables, the method could not yet gain wide acceptance.
Kosfeld, Reinhold +1 more
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Analytical Chemistry, 2001
Bilinear data matrices may be resolved into abstract factors by factor analysis. The underlying chemical processes that generated the data may be deduced from the abstract factors by hard (model fitting) or soft (model-free) analyses. We propose a novel approach that combines the advantages of both hard and soft methods, in that only a few parameters ...
Mason, Caroline +2 more
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Bilinear data matrices may be resolved into abstract factors by factor analysis. The underlying chemical processes that generated the data may be deduced from the abstract factors by hard (model fitting) or soft (model-free) analyses. We propose a novel approach that combines the advantages of both hard and soft methods, in that only a few parameters ...
Mason, Caroline +2 more
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Factor Analysis for Anonymization
2017 IEEE International Conference on Data Mining Workshops (ICDMW), 2017In this paper we propose a new method to anonymize (share relevant and detailed information while not naming names) and protect data sets (minimize the utility loss) based on Factor Analysis. The method basically consists of obtaining the factors, which are uncorrelated, protecting them and undoing the transformation in order to get interpretable ...
Calvino, Aida +2 more
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Neural Computation, 1999
We introduce the independent factor analysis (IFA) method for recovering independent hidden sources from their observed mixtures. IFA generalizes and unifies ordinary factor analysis (FA), principal component analysis (PCA), and independent component analysis (ICA), and can handle not only square noiseless mixing but also the general case where the ...
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We introduce the independent factor analysis (IFA) method for recovering independent hidden sources from their observed mixtures. IFA generalizes and unifies ordinary factor analysis (FA), principal component analysis (PCA), and independent component analysis (ICA), and can handle not only square noiseless mixing but also the general case where the ...
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FACTOR INTERACTION IN NONLINEAR FACTOR ANALYSIS
British Journal of Mathematical and Statistical Psychology, 1967Factor interaction models are defined as those cases in nonlinear factor analysis in which the specification equation contains products of two or more latent variables or functions of latent variables. A complete algebraic treatment is given for the case of a product of two latent variables, and certain more general cases are briefly outlined.
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