The concept of sequential estimation is introduced in multidimensional scaling. The sequential estimation method developed in this paper refers to continually updating estimates of a configuration as new observations are added. Using artificial data, the performance of this sequential method is illustrated. (Author/JKS)

Using constraints with cluster analysis limits the possible number of clusters. This paper deals with clustering problems where grouping is constrained by a symmetric and reflexive relation. Two approaches, along with illustrations, are presented. (Author/JKS)

A general class of nonhierarchical clustering models and associated algorithms for fitting them are presented. These models generalize the Shepard-Arabie Additive clusters model. Two applications are given and extensions to three-way models, nonmetric analyses, and other model specifications are provided. (Author/JKS)

Results of analysis of 1,377 spelling error forms including three categories of spelling errors (consonantal, vowel, and sequential) demonstrate that majority of spelling errors are highly predictable when set of predefined rules based on phonological and sequential considerations are followed algorithmically. Eleven references and equivalent…

Presents a model for schools based on the transmission of algorithms (a set of problem-solving procedures) through computers. Sample lesson series are provided, as well as a description of special teacher qualifications required and the benefits of such a program. (Author/WD)

Monte Carlo validation studies of clustering algorithms, including Ward's minimum variance hierarchical method, are reviewed. Caution concerning the uncritical selection of Ward's method for recovering cluster structure is advised. Alternative explanations for differential recovery performance are explored and recommendations are made for future…

A method for externally constraining certain distances in multidimensional scaling configurations is introduced and illustrated. The method is described in detail and several examples are presented. (Author/JKS)

A new algorithm is used to test and describe the set of all possible solutions for any linear model of an empirical ordering derived from techniques such as additive conjoint measurement, unfolding theory, general Fechnerian scaling, and ordinal multiple regression. The algorithm is computationally faster and numerically superior to previous…

Discussion of text compression focuses on a method to reduce the amount of storage needed to represent a Markov model with an extended alphabet, by applying a clustering scheme that brings together similar states. Highlights include probability vectors; algorithms; implementation details; and experimental data with natural languages. (Author/LRW)

Explains transliteration and describes Greeklish, a Windows application that automatically produces English to Greek transliteration and back-transliteration (retransliteration), based on an algorithm with a table of associations between the two character sets. Describes how the table can be modified for personal preferences and discusses its…

Presents recently developed generalizations to the sieve of Eratosthenes, showing the principles underlying these improvements, which increase its efficiency without changing too much of its simplicity. Offers several possibilities to propose good investigations for students to explore, find patterns, and make generalizations. (JRH)