Robust density estimation using distance methods

Peter J. Diggle

Research output: Contribution to journalArticlepeer-review

Abstract

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
JournalBiometrika
Volume62
Issue number1
DOIs
StatePublished - Apr 1975
Externally publishedYes

Keywords

  • 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)

Fingerprint Dive into the research topics of 'Robust density estimation using distance methods'. Together they form a unique fingerprint.

Cite this