Environmental and Ecological Statistics

, Volume 2, Issue 4, pp 305–313 | Cite as

A capture-recapture model with heterogeneity and behavioural response

  • James L. NorrisIII
  • Kenneth H. Pollock


We develop the non-parametric maximum likelihood estimator (MLE) of the full Mbh capture-recapture model which utilizes both initial capture and recapture data and permits both heterogeneity (h) between animals and behavioural (b) response to capture. Our MLE procedure utilizes non-parametric maximum likelihood estimation of mixture distributions (Lindsay, 1983; Lindsay and Roeder, 1992) and the EM algorithm (Dempsteret al., 1977). Our MLE estimate provides the first non-parametric estimate of the bivariate capture-recapture distribution.

Since non-parametric maximum likelihood estimation exists for submodels Mh (allowing heterogeneity only), Mb (allowing behavioural response only) and M0 (allowing no changes), we develop maximum likelihood-based model selection, specifically the Akaike information criterion (AIC) (Akaike, 1973). The AIC procedure does well in detecting behavioural response but has difficulty in detecting heterogeneity.


Bivariate distribution bootstrap EM algorithm mixture distribution 


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Copyright information

© Chapman & Hall 1995

Authors and Affiliations

  • James L. NorrisIII
    • 1
  • Kenneth H. Pollock
    • 2
  1. 1.Department of Mathematics and Computer ScienceWake Forest UniversityWinston-SalemUSA
  2. 2.Department of StatisticsNorth Carolina State UniversityRaleighUSA

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