BayMDS: An R Package for Bayesian Multidimensional Scaling and Choice of Dimension

Research output: Contribution to journalComment/debate

1 Scopus citations
Original languageEnglish
Pages (from-to)250-251
Number of pages2
JournalApplied Psychological Measurement
Issue number3
StatePublished - May 2022

Bibliographical note

Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Basic Science Research Program (2019R1A2C1003086 and 2019R1A6A1A11051177 for M-S Oh; 2018R1A2B6001251 for E-K Lee) through the National Research Foundation of Korea (NRF) funded by the Korean government (MIST).


  • Bayesian dimension selection
  • dissimilarity
  • multidimensional scaling
  • object configuration

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