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The VGAM Package for Capture-Recapture Data Using the Conditional Likelihood

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  • Yee, Thomas W.
  • Stoklosa, Jakub
  • Huggins, Richard M.

Abstract

It is well known that using individual covariate information (such as body weight or gender) to model heterogeneity in capture-recapture (CR) experiments can greatly enhance inferences on the size of a closed population. Since individual covariates are only observable for captured individuals, complex conditional likelihood methods are usually required and these do not constitute a standard generalized linear model (GLM) family. Modern statistical techniques such as generalized additive models (GAMs), which allow a relaxing of the linearity assumptions on the covariates, are readily available for many standard GLM families. Fortunately, a natural statistical framework for maximizing conditional likelihoods is available in the Vector GLM and Vector GAM classes of models. We present several new R functions (implemented within the VGAM package) specifically developed to allow the incorporation of individual covariates in the analysis of closed population CR data using a GLM/GAM-like approach and the conditional likelihood. As a result, a wide variety of practical tools are now readily available in the VGAM object oriented framework. We discuss and demonstrate their advantages, features and flexibility using the new VGAM CR functions on several examples.

Suggested Citation

  • Yee, Thomas W. & Stoklosa, Jakub & Huggins, Richard M., 2015. "The VGAM Package for Capture-Recapture Data Using the Conditional Likelihood," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 65(i05).
    • Handle: RePEc:jss:jstsof:v:065:i05
    DOI: http://hdl.handle.net/10.18637/jss.v065.i05
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    References listed on IDEAS

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    1. Jakub Stoklosa & Wen-Han Hwang & Sheng-Hai Wu & Richard Huggins, 2011. "Heterogeneous Capture–Recapture Models with Covariates: A Partial Likelihood Approach for Closed Populations," Biometrics, The International Biometric Society, vol. 67(4), pages 1659-1665, December.
    2. Richard Huggins & Wen‐Han Hwang, 2007. "Non‐parametric estimation of population size from capture–recapture data when the capture probability depends on a covariate," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(4), pages 429-443, August.
    3. Baillargeon, Sophie & Rivest, Louis-Paul, 2007. "Rcapture: Loglinear Models for Capture-Recapture in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 19(i05).
    4. Stoklosa, Jakub & Huggins, Richard M., 2012. "A robust P-spline approach to closed population capture–recapture models with time dependence and heterogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 408-417.
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