Robust density estimation using distance methods

Peter J. Diggle

Research output: Contribution to journalArticlepeer-review

52 Scopus citations


Distance estimators of density may exhibit serious bias unless the population under consideration forms a completely random spatial pattern, i.e. the estimators are not robust. In this paper some new estimators are proposed, and their robustness is assessed analytically against two stochastic models, which together embrace a continuous range of spatial pattern, from extreme regularity, through randomness, to extreme aggregation.

Original languageEnglish (US)
Pages (from-to)39-48
Number of pages10
Issue number1
StatePublished - Apr 1975
Externally publishedYes


  • Density estimation
  • Distance method
  • Ecology
  • Robustness
  • Spatial distribution

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Mathematics(all)
  • Statistics and Probability
  • Agricultural and Biological Sciences (miscellaneous)
  • Agricultural and Biological Sciences(all)


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