Abstract
Distance sampling provides a rigorous framework for estimating detectability, allowing us to correct counts of detected animals in covered areas for those that were missed. The fundamental concept involved in estimating detectability in the distance sampling context is the detection function, which represents the probability of detecting an object of interest as a function of its distance from the line or point. Thus a key step in any distance sampling analysis is to choose a plausible and parsimonious model for the detection function.
The original version of this chapter was revised. An erratum to this chapter can be found at https://doi.org/10.1007/978-3-319-19219-2_14.
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Buckland, S.T., Rexstad, E.A., Marques, T.A., Oedekoven, C.S. (2015). Modelling Detection Functions. In: Distance Sampling: Methods and Applications. Methods in Statistical Ecology. Springer, Cham. https://doi.org/10.1007/978-3-319-19219-2_5
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DOI: https://doi.org/10.1007/978-3-319-19219-2_5
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