Incorporating Covariates into Standard Line Transect Analyses

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159 Citations (Scopus)

Abstract

An implicit assumption of standard line transect methodology is that detection probabilities depend solely on the perpendicular distance of detected objects to the transect line. Heterogeneity in detection probabilities is commonly minimized using stratification, but this may be precluded by small sample sizes. We develop a general methodology which allows the effects of multiple covariates to be directly incorporated into the estimation procedure using a conditional likelihood approach. Small sample size properties of estimators are examined via simulations. As an example the method is applied to eastern tropical Pacific dolphin sightings data.

Original languageEnglish
Pages (from-to)924-935
Number of pages12
JournalBiometrics
Volume59
Issue number4
DOIs
Publication statusPublished - Dec 2003

Keywords

  • abundance estimation
  • line transect sampling
  • size bias
  • SIZE BIAS
  • IN-LINE
  • ABUNDANCE
  • MODELS
  • TUNA

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