Results 211 to 220 of about 25,062,635 (240)
Some of the next articles are maybe not open access.
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.
openaire +2 more sources
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
openaire +2 more sources
Psychometrika, 1987
The information criterion AIC was introduced to extend the method of maximum likelihood to the multimodel situation. It was obtained by relating the successful experience of the order determination of an autoregressive model to the determination of the number of factors in the maximum likelihood factor analysis.
openaire +1 more source
The information criterion AIC was introduced to extend the method of maximum likelihood to the multimodel situation. It was obtained by relating the successful experience of the order determination of an autoregressive model to the determination of the number of factors in the maximum likelihood factor analysis.
openaire +1 more source
2012
We build on investigations by Keprt, Snasel, Belohlavek, and Vychodil on Boolean Factor Analysis. Rather than minimising the number of Boolean factors we aim at many-valued factorisations with a small number of ordinal factors.
Bernhard Ganter, Cynthia Vera Glodeanu
openaire +1 more source
We build on investigations by Keprt, Snasel, Belohlavek, and Vychodil on Boolean Factor Analysis. Rather than minimising the number of Boolean factors we aim at many-valued factorisations with a small number of ordinal factors.
Bernhard Ganter, Cynthia Vera Glodeanu
openaire +1 more source
Heteroscedastic factor analysis
Biometrika, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lewin-Koh, S.-C., Amemiya, Y.
openaire +2 more sources
Multivariate Behavioral Research, 1968
-When a set of variables cannot be regarded as being drawn from a well defined population, the estimation of communalities, population parameters, and universe factors is not a rational undertaking. A descriptive factor analysis can be performed by weighting test vectors inversely as the components of total test variance unable to determine a test ...
openaire +2 more sources
-When a set of variables cannot be regarded as being drawn from a well defined population, the estimation of communalities, population parameters, and universe factors is not a rational undertaking. A descriptive factor analysis can be performed by weighting test vectors inversely as the components of total test variance unable to determine a test ...
openaire +2 more sources
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
openaire +2 more sources
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
openaire +2 more sources
Evidence Based Mental Health, 2008
Factor analysis is a broad term that refers to a set of statistical methods used to detect underlying patterns in the relationships among a number of observed variables. Its origins were in the large scale studies defining the dimensions of intelligence pioneered by Thurstone.1 ,2 Factor analysis can appear complicated to the general reader but the ...
openaire +2 more sources
Factor analysis is a broad term that refers to a set of statistical methods used to detect underlying patterns in the relationships among a number of observed variables. Its origins were in the large scale studies defining the dimensions of intelligence pioneered by Thurstone.1 ,2 Factor analysis can appear complicated to the general reader but the ...
openaire +2 more sources
Profile Factor Analysis and Variable Factor Analysis
Psychological Reports, 1964Nunnally (1962) mentions three types of profile factor analyses: correlational, covariance, and raw score sums of crossproducts. When principal components factors are used, each of these profile analyses corresponds to a precisely equivalent factor analysis of variables.
openaire +1 more source
The Development of Factor Analysis
The Journal of General Psychology, 1958(1958). The Development of Factor Analysis. The Journal of General Psychology: Vol. 58, No. 2, pp. 139-164.
openaire +2 more sources