Journal ArticleDOI
I-Scal: Multidimensional scaling of interval dissimilarities
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TLDR
A new algorithm called I-Scal, based on iterative majorization, that has the advantage that each iteration is guaranteed to improve the solution until no improvement is possible is developed.About:
This article is published in Computational Statistics & Data Analysis.The article was published on 2006-11-01. It has received 46 citations till now. The article focuses on the topics: Multidimensional scaling & Interval (mathematics).read more
Citations
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Journal ArticleDOI
Multidimensional scaling with the nested hypersphere model for percentile dissimilarities
TL;DR: A necessary and sufficient condition for that two hyperspheres are nested is derived and a new MDS model for dissimilarities described by percentile intervals is proposed, which is used for representing an object.
Journal ArticleDOI
Book review of: 'The Fuzzy Approach to Statistical Analysis' (A special Issue of the Journal of Computational Statistics and Data Analysis), vol. 51(1), ISSN 0167-9473, 2006 (pp. 1–452)
Proceedings ArticleDOI
Algebraic confidence in positioning problems
TL;DR: The results show that the proposed extended CIS cost function, called CIS;, dramatically improve the estimates over the targets' locations, and is shown to compensate eventual NLOS range measurements without need for any bias identification algorithm.
Journal Article
Comparison of forescasting methods for interval-valued time series
TL;DR: The study aims to obtain new time series forecasting methods using different combination of several analysis methods and modeling techniques and to determine the methods and models that provide the optimal accuracy by comparing the forecasting accuracy of the proposed methods.
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Assessment of the Development of the European Oecd Countries with the Application of Linear Ordering and Ensemble Clustering of Symbolic Data
TL;DR: Assessment of the development of the selected European OECD countries with the application of the linear ordering and ensemble clustering of symbolic data as well as comparison of thesemble clustering with a single model show that ensemble clusters for symbolic data can be a useful tool in country development analysis.
References
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Journal ArticleDOI
Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis
TL;DR: The fundamental hypothesis is that dissimilarities and distances are monotonically related, and a quantitative, intuitively satisfying measure of goodness of fit is defined to this hypothesis.
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Nonmetric multidimensional scaling: A numerical method
TL;DR: The numerical methods required in the approach to multi-dimensional scaling are described and the rationale of this approach has appeared previously.
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Some distance properties of latent root and vector methods used in multivariate analysis
TL;DR: In this paper, the authors derived necessary and sufficient conditions for a solution to exist in real Euclidean space for a multivariate multivariate sample of size n as points P1, P2,..., PI in a Euclidian space and discussed the interpretation of the distance A(Pi, Pj) between the ith and jth members of the sample.
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Modern Multidimensional Scaling: Theory and Applications
TL;DR: The four Purposes of Multidimensional Scaling, Special Solutions, Degeneracies, and Local Minima, and Avoiding Trivial Solutions in Unfolding are explained.