Please use this identifier to cite or link to this item: https://doi.org/10.1023/A:1009623301208
Title: Animal abundance estimation in independent observer line transect surveys
Authors: Chen, S.X. 
Keywords: Conditional likelihood
Kernel smoothing
Line transect survey
Issue Date: 2000
Citation: Chen, S.X. (2000). Animal abundance estimation in independent observer line transect surveys. Environmental and Ecological Statistics 7 (3) : 285-299. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1009623301208
Abstract: The theory of conventional line transect surveys is based on an essential assumption that 100% detection of animals right on the transect lines can be achieved. When this assumption fails, independent observer line transect surveys are used. This paper proposes a general approach, based on a conditional likelihood, which can be carried out either parametrically or nonparametrically, to estimate the abundance of non-clustered biological populations using data collected from independent observer line transect surveys. A nonparametric estimator is specifically proposed which combines the conditional likelihood and the kernel smoothing method. It has the advantage that it allows the data themselves to dictate the form of the detection function, free of any subjective choice. The bias and the variance of the nonparametric estimator are given. Its asymptotic normality is established which enables construction of confidence intervals. A simulation study shows that the proposed estimator has good empirical performance, and the confidence intervals have good coverage accuracy.
Source Title: Environmental and Ecological Statistics
URI: http://scholarbank.nus.edu.sg/handle/10635/105005
ISSN: 13528505
DOI: 10.1023/A:1009623301208
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