Descriptor
Algorithms | 4 |
Least Squares Statistics | 4 |
Multiple Regression Analysis | 4 |
Mathematical Models | 2 |
Regression (Statistics) | 2 |
Statistical Analysis | 2 |
Analysis of Variance | 1 |
Educational Research | 1 |
Equations (Mathematics) | 1 |
Graphs | 1 |
Measurement Techniques | 1 |
More ▼ |
Publication Type
Reports - Research | 4 |
Journal Articles | 3 |
Opinion Papers | 1 |
Speeches/Meeting Papers | 1 |
Education Level
Audience
Researchers | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating

Fornell, Claes; And Others – Multivariate Behavioral Research, 1988
This paper shows that redundancy maximization with J. K. Johansson's extension can be accomplished via a simple iterative algorithm based on H. Wold's Partial Least Squares. The model and the iterative algorithm for the least squares approach to redundancy maximization are presented. (TJH)
Descriptors: Algorithms, Equations (Mathematics), Least Squares Statistics, Mathematical Models

Shapiro, Jonathan – American Educational Research Journal, 1979
Contrary to Anderson (EJ 187 936), his rule for equation identification is a necessary but not sufficient condition; furthermore, the choice of two-stage or ordinary least squares depends on results and not on methodological properties of estimators. Modification of Anderson's rule and a means for choosing between estimates is offered. (Author/CP)
Descriptors: Algorithms, Educational Research, Least Squares Statistics, Mathematical Models

Tenenhaus, Michel – Psychometrika, 1988
Canonical analysis of two convex polyhedral cones involves looking for two vectors whose square cosine is a maximum. New results about the properties of the optimal solution to this problem are presented. The convergence of an alternating least squares algorithm and properties of limits of calculated sequences are discussed. (SLD)
Descriptors: Algorithms, Analysis of Variance, Graphs, Least Squares Statistics
Morris, John D. – 1986
An empirical method called Predicted Error Sum of Squares (PRESS) is advanced and studied. This method is used to examine the cross-validated prediction accuracies of some popular algorithms for weighted predictor variables. The weighting methods that were considered were ordinary least squares, ridge regression, regression on principal…
Descriptors: Algorithms, Least Squares Statistics, Measurement Techniques, Minicomputers