Skip to main content

Inference with Median Distances: An Alternative to Reduce the Influence of Outlier Populations

  • Chapter
  • First Online:
Trends in Mathematical, Information and Data Sciences

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 445))

  • 390 Accesses

Abstract

In multivariate analysis, the measures of similarity and distance characterize the analogies and differences between objects. Based on the distances, a medoids test uses diversity to characterize the variabilities between and within groups. To reduce the distorting effect of outlier populations, we propose an alternative based on medians. To be precise, the medoid of each group has been related to the object that minimizes the median of the distances to the other members of the group, and the diversity within each group has been related to the median of the distances to the medoid. In this context, the distribution of the ratio of the diversities (between and within groups) is obtained by the method of permutations. The results obtained in a simulation study of a prospective character have established that, in the presence of outlier populations, the test based on medians provides a greater adherence to the level of significance (\(\alpha =0.05\)) than the test based on means.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Anderson, M.J.: A new method for nonparametric multivariate analysis of variance. Austral. Ecol. 26(1), 32–46 (2001)

    Google Scholar 

  2. Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E.: Multivariate Data Analysis: A Global Perspective. Prentice Hall, Upper Saddle River (2009)

    Google Scholar 

  3. Pardo, L.: Statistical Inference Based on Divergence Measures. Chapman & Hall/CRC, Boca Raton (2006)

    MATH  Google Scholar 

  4. Salicrú, M., Morales, D., Menéndez, M.L., Pardo, L.: On the applications of divergence type measures in testing statistical hypotheses. J. Multivar. Anal. 51(2), 372–391 (1994)

    Article  MathSciNet  Google Scholar 

  5. Salicrú, M., Vives, S., Ocaña, J.: Testing the homogeneity of diversity measures: a general framework. J. Statist. Plan. Infer. 132(1–2), 117–129 (2005)

    Article  MathSciNet  Google Scholar 

  6. Seber, G.A.: Multivariate Observations. Wiley, New York (2009)

    MATH  Google Scholar 

  7. Timm, N.H.: Applied Multivariate Analysis. Springer, New York (2002)

    MATH  Google Scholar 

Download references

Acknowledgements

This work was supported by the Ministerio de Ciencia, Innovación y Universidades (Spain) under Grant PID2019-104830RB-I00 and the Departament d’Empresa i Coneixement de la Generalitat de Catalunya (Spain) under Grant 2017 SGR 622 (GRBIO).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Miquel Salicrú .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Salicrú, M., Reverter, F., Besalú, M., Burset, M. (2023). Inference with Median Distances: An Alternative to Reduce the Influence of Outlier Populations. In: Balakrishnan, N., Gil, M.Á., Martín, N., Morales, D., Pardo, M.d.C. (eds) Trends in Mathematical, Information and Data Sciences. Studies in Systems, Decision and Control, vol 445. Springer, Cham. https://doi.org/10.1007/978-3-031-04137-2_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-04137-2_37

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-04136-5

  • Online ISBN: 978-3-031-04137-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics