A nonspatial operationalization of the Krumhansl distance-density model of similarity is presented. The conceptual model and empirical evidence are reviewed. A nonspatial, tree-fitting methodology is described, which is sufficiently flexible to fit several competing hypotheses of similarity formation. Extensions to spatial models, three-way…

Evaluated the performance of several alternative cluster analytic approaches to initial model specification using population parameter analyses and a Monte Carlo simulation. Of the six cluster approaches evaluated, the one using the correlations of item correlations as a proximity metric and average linking as a clustering algorithm performed the…

A probabilistic model of keyword indexing is outlined, and some of the consequences of the model are examined. An algorithm defining a measure of indexability is developed--a measure intended to reflect the relative significance of words in documents. (Author)

Estimation of ability and item parameters in latent trait models is discussed. When both ability and item parameters are considered fixed but unknown, the method of maximum likelihood for the logistic or probit models is well known. Discussed are techniques for estimating ability and item parameters when the ability parameters or item parameters…

A description of a Mokken test program to test the robustness of nonparametric Stochastic scales is presented. For each sample and the whole population, different scale statistics (both on scale and on item level) are computed recursively. A statistic T is presented for testing the robustness of the scales in the samples. (Author)

A model for the analysis of paired comparison data is presented which is metric, mathematically tractable, and has an exact algebraic solution. (Authors/MB)

A procedure is outlined showing how the axiom of local independence for latent structure models can be weakened. (CK)

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)

Reports on the validity of the Multiple Poisson (nP) model of word distribution in full-text document collections. A practical algorithm for determining whether a certain word is distributed according to an nP distribution and the results of a test of this algorithm in three different document collections are described. (14 references) (KRN)

An algorithm based on the majorization theory of J. de Leeuw and W. J. Heiser is presented for fitting the slide-vector model. It views the model as a constrained version of the unfolding model. A three-way variant is proposed, and two examples from market structure analysis are presented. (SLD)

A new procedure is proposed for handling nominal variables in the analysis of variables of mixed measurement levels, and a procedure is developed for handling ordinal variables. Using these procedures, a monotonically convergent algorithm is constructed for the FACTALS method for any mixture of variables. (SLD)

This paper presents a detailed description of maximum parameter estimation for item response models using the general EM algorithm. In this paper the models are specified using a univariate discrete latent ability variable. When the latent ability variable is discrete the distribution of the observed item responses is a finite mixture, and the EM…

The probability integral of the multivariate normal distribution (ND) has received considerable attention since W. F. Sheppard's (1900) and K. Pearson's (1901) seminal work on the bivariate ND. This paper evaluates the formula that represents the "n x n" correlation matrix of the "chi(sub i)" and the standardized multivariate…

THIS NOTE PRESENTS MODELS FOR PASSING JUDGMENT ON THE IMPORTANCE OF PROJECTS. TWO APPROACHES ARE CONSIDERED--PROJECTS WITH TWO ATTRIBUTES, PRIORITY AND DEADLINE DATES, AND PROJECTS WITH K ATTRIBUTES. THE SOLUTIONS ARE ILLUSTRATED THROUGH EXAMPLES AND BY AN ALGORITHM PRESENTED IN A COMPUTER REFERENCE LANGUAGE TO SHOW HOW ONE OF THE SOLUTIONS CAN BE…

The intent of this paper is to generalize the min and max clustering procedures in such a way that the assumption of a symmetric similarity measure is unnecessary. (Author)