Although the assignment was to write a note about the famous, highly cited Kruskal 1964 papers, it would hardly be fair if the topic wasn’t described in the context of two other papers, being Shepard’s 1962 papers (with 2309 citations in Google Scholar as of 4/1/2016) that started the development of what is called nonmetric multidimensional scaling. Before getting into more detail, some of the ...

This paper presents results regarding the performance of multidimensional scaling (MDS) when used to create three-dimensional navigation maps. MDS aims at reducing high-dimensional space into low-dimensional landscapes. Combined with browsers which are capable of visualizing threedimensional object information by applying the conceptual basis of Virtual Reality Modeling Language (VRML), MDS ope...

Multidimensional scaling (MDS) is the process of transforming a set of points in a high-dimensional space to a lower-dimensional one while preserving the relative distances between pairs of points. Although effective methods have been developed for solving a variety of MDS problems, they mainly depend on the vectors in the lower-dimensional space having real-valued components. For some applicat...

SUMMARY We present bammds, a practical tool that allows visualization of samples sequenced by second-generation sequencing when compared with a reference panel of individuals (usually genotypes) using a multidimensional scaling algorithm. Our tool is aimed at determining the ancestry of unknown samples-typical of ancient DNA data-particularly when only low amounts of data are available for thos...

Restorative and scaling treatments have not generally provided an effective method for managing dental caries and periodontal diseases. Rather, restorative treatment has often covered up the disease processes in the short term and created a new problem: that of maintenance and re-restoration of restored teeth. Thus, standard invasive dental treatments that are commonly provided fail to address ...

Mathematical models for the prediction of company failure are by now well established . Most of the work on multivariate modelling of distress prediction attempts to obtain a score that gives the failure probability of a company. A data set of 66 Spanish banks , 29 of which failed , is used to show that multidimensional scaling (MDS) techniques can be of use to produce simple tools for the anal...

Population counts and longitude and latitude coordinates were estimated for the 50 largest cities in the United States by computational linguistic techniques and by human participants. The mathematical technique Latent Semantic Analysis applied to newspaper texts produced similarity ratings between the 50 cities that allowed for a multidimensional scaling (MDS) of these cities. MDS coordinates ...

Dental crowding is defined as a discrepancy between tooth size and jaw size that results in a misalignment of the tooth row. Proposed reasons for crowding include excessively large teeth, small jaws, and a combination of both. Nevertheless, the parameters that would allow the prediction of crowding have not been identified. This study compared the shape of crowded and uncrowded dental arches, m...

We detail the investigation of the first application of several dissimilarity measures for large-scale solar image data analysis. Using a solar-domain-specific benchmark dataset that contains multiple types of phenomena, we analyzed combinations of image parameters with different dissimilarity measures in order to determine which combinations will allow us to differentiate among the multiple so...

Tversky's contrast model of proximity was initially formulated to account for the observed violations of the metric axioms often found in empirical proximity data. This set-theoretic approach models the similarity/dissimilarity between any two stimuli as a linear (or ratio) combination of measures of the common and distinctive features of the two stimuli. This paper proposes a new spatial multi...