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A Guide for Sparse PCA: Model Comparison and Applications
PCA is a popular tool for exploring and summarizing multivariate data, especially those consisting of many variables. PCA, however, is often not...
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A Model-Based Approach for Visualizing the Dimensional Structure of Ordered Successive Categories Preference Data
A cyclical conditional maximum likelihood estimation procedure is developed for the multidimensional unfolding of two- or three-way dominance data...
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The Determinants of the Bias in Minimum Rank Factor Analysis (MRFA)
Minimum Rank Factor Analysis (MRFA), see Ten Berge (1998), and Ten Berge and Kiers (1991), is a method of common factor analysis which yields, for...
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Statistical inference of minimum rank factor analysis
For any given number of factors, Minimum Rank Factor Analysis yields optimal communalities for an observed covariance matrix in the sense that the...
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The asymptotic bias of minimum trace factor analysis, with applications to the greatest lower bound to reliability
In theory, the greatest lower bound (g.l.b.) to reliability is the best possible lower bound to the reliability based on single test administration....
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The tunneling method for global optimization in multidimensional scaling
This paper focuses on the problem of local minima of the STRESS function. It turns out that unidimensional scaling is particularly prone to local...
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A monotonically convergent algorithm for orthogonal congruence rotation
Brokken has proposed a method for orthogonal rotation of one matrix such that its columns have a maximal sum of congruences with the columns of a...
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Maximization of sums of quotients of quadratic forms and some generalizations
Monotonically convergent algorithms are described for maximizing six (constrained) functions of vectors x, or matrices X with columns x 1 , ..., x ...
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Specification and Estimation of Mean Structures: Regression Models
A major activity in the social sciences is modeling the dependence of one or more outcome or dependent variables on some explanatory or predictor...
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An alternating least squares method for the weighted approximation of a symmetric matrix
Bailey and Gower examined the least squares approximation C to a symmetric matrix B , when the squared discrepancies for diagonal elements receive...
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Minimization of a class of matrix trace functions by means of refined majorization
A procedure is described for minimizing a class of matrix trace functions. The procedure is a refinement of an earlier procedure for minimizing the...
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Alternative common factor models for multivariate biometric analyses
In prior research we have shown how linear structural equation models and computer programs (e.g., LISREL) may be simply and directly used to provide...
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Some properties of estimated scale invariant covariance structures
Scale invariance is a property shared by many covariance structure models employed in practice. An example is provided by the well-known LISREL model...
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Problems with EM algorithms for ML factor analysis
Rubin and Thayer recently presented equations to implement maximum likelihood (ML) estimation in factor analysis via the EM algorithm. They present...
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Constrained canonical correlation
This paper explores some of the problems associated with traditional canonical correlation. A response surface methodology is developed to examine...
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Application of optimal sign-vectors to reliability and cluster analysis
Expressions involving optimal sign vectors are derived so as to yield two new applications. First, coefficient alpha for the sign-weighted composite...
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On meredith's solution for weighted procrustes rotation
Meredith developed a criterion for weighted procrustes rotation. The solution was given using Lagrange multipliers. We show that the solution can be...
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The problem of the additive constant and eigenvalues in metric multidimensional scaling
This paper is concerned with the additive constant problem in metric multidimensional scaling. First the influence of the additive constant on...
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A random search algorithm for laboratory computers
The small laboratory computer is ideal for experimental control and data acquisition. Postexperimental data processing is many times performed on...