Results 211 to 220 of about 5,200,900 (248)
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Psychometrika, 1965
A distinction is made between statistical inference and psychometric inference in factor analysis. After reviewing Rao's canonical factor analysis (CFA), a fundamental statistical method of factoring, a new method of factor analysis based upon the psychometric concept of generalizability is described.
Kaiser, Henry F., Caffrey, J.
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A distinction is made between statistical inference and psychometric inference in factor analysis. After reviewing Rao's canonical factor analysis (CFA), a fundamental statistical method of factoring, a new method of factor analysis based upon the psychometric concept of generalizability is described.
Kaiser, Henry F., Caffrey, J.
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Fisher Discriminant Analysis and Factor Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1983We show that information on the inherent structure of multidimensional data derived from a factor analysis procedure is equivalent to information obtained by Fisher discriminant analysis techniques, provided certain conditions, usually required in the factor analysis model, are satisfied.
Giacomo Della Riccia +1 more
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Regression and Factor Analysis
Biometrika, 1973SUMMARY A basic model of factor analysis is employed in the estimation of multiple correlation coefficients and partial regression weights. Estimators are derived for situations in which some or all of the independent variates are subject to errors in measurement.
Lawley, D. N., Maxwell, A. E.
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Journal of Chemical Information and Computer Sciences, 1979
Abstract : Principal components and other standard factor analyses can yield misleading results if an assumed subsidiary condition is untrue or if data are missing. Principal components factor analysis is tested for its reliability, using a problem with known answers.
C. Gardner Swain +2 more
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Abstract : Principal components and other standard factor analyses can yield misleading results if an assumed subsidiary condition is untrue or if data are missing. Principal components factor analysis is tested for its reliability, using a problem with known answers.
C. Gardner Swain +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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British Journal of Mathematical and Statistical Psychology, 1970
It is shown that PFA, CFA and AFA are particular cases of a scale‐invariant factoring procedure based on variance ratios of certain weighted combinations of variables. Standard derivations in the literature are shown, in contrast, to have unsatisfactory features.
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It is shown that PFA, CFA and AFA are particular cases of a scale‐invariant factoring procedure based on variance ratios of certain weighted combinations of variables. Standard derivations in the literature are shown, in contrast, to have unsatisfactory features.
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Heteroscedastic factor analysis
Biometrika, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lewin-Koh, S.-C., Amemiya, Y.
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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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Statistical Papers, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kosfeld, Reinhold +1 more
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kosfeld, Reinhold +1 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 ...
Aida Calvino +2 more
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