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Fitting the Off-Diagonal DEDICOM Model in the Least-Squares Sense by a Generalization of the Harman and Jones MINRES Procedure of Factor Analysis.
Peer reviewed Peer reviewed
ten Berge, Jos M. F.; Kiers, Henk A. L. – Psychometrika, 1989
The DEDICOM (decomposition into directional components) model provides a framework for analyzing square but asymmetric matrices of directional relationships among "n" objects or persons in terms of a small number of components. One version of DEDICOM ignores the diagonal entries of the matrices. A straightforward computational solution…
Descriptors: Algorithms, Factor Analysis, Goodness of Fit, Least Squares Statistics
Alternative Measures of Fit for The Schonemann-Caroll Matrix Fitting Algorithm
Peer reviewed Peer reviewed
Lingoes, James C.; Schonemann, Peter H. – Psychometrika, 1974
Descriptors: Algorithms, Goodness of Fit, Matrices, Orthogonal Rotation
A Fortran IV Program Generalizing the Schonemann-Carroll Matrix Fitting Algorithm to Monotone and Linear Fitting of Configurations
Peer reviewed Peer reviewed
Lingoes, James C. – Journal of Educational and Psychological Measurement, 1974
Descriptors: Algorithms, Computer Programs, Factor Analysis, Goodness of Fit
Statistical Methods for Absorbing Markov-Chain Models For Learning: Estimation And Identification
Peer reviewed Peer reviewed
Polson, Peter G.; Huizinga, David – Psychometrika, 1974
Descriptors: Algorithms, Computer Programs, Goodness of Fit, Learning Processes
Weighted Least Squares Fitting Using Ordinary Least Squares Algorithms.
Peer reviewed Peer reviewed
Kiers, Henk A. L. – Psychometrika, 1997
A general approach for fitting a model to a data matrix by weighted least squares (WLS) is studied. The approach consists of iteratively performing steps of existing algorithms for ordinary least squares fitting of the same model and is based on maximizing a function that majorizes WLS loss function. (Author/SLD)
Descriptors: Algorithms, Goodness of Fit, Least Squares Statistics, Mathematical Models
Some Clarifications of the TUCKALS2 Algorithm Applied to the IDIOSCAL Problem.
Peer reviewed Peer reviewed
Ten Berge, Jos M. F.; And Others – Psychometrika, 1994
The suggestion that the IDIOSCAL model be fitted by the TUCKALS2 algorithm for three-way components analysis is examined. The claim that resulting coordinate matrices will be identical is supported when the data matrices are semidefinite. Counterexamples for indefinite matrices are also constructed. (SLD)
Descriptors: Algorithms, Correlation, Equations (Mathematics), Goodness of Fit