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  • 标题:More on Multidimensional Scaling and Unfolding in R: smacof Version 2
  • 本地全文:下载
  • 作者:Patrick Mair ; Patrick J. F. Groenen ; Jan de Leeuw
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2022
  • 卷号:102
  • 页码:1-47
  • DOI:10.18637/jss.v102.i10
  • 语种:English
  • 出版社:University of California, Los Angeles
  • 摘要:The smacof package offers a comprehensive implementation of multidimensional scaling (MDS) techniques in R. Since its first publication (De Leeuw and Mair 2009b) the functionality of the package has been enhanced, and several additional methods, features and utilities were added. Major updates include a complete re-implementation of multidimensional unfolding allowing for monotone dissimilarity transformations, including row-conditional, circular, and external unfolding. Additionally, the constrained MDS implementation was extended in terms of optimal scaling of the external variables. Further package additions include various tools and functions for goodness-of-fit assessment, unidimensional scaling, gravity MDS, asymmetric MDS, Procrustes, and MDS biplots. All these new package functionalities are illustrated using a variety of real-life applications.
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