
doi: 10.2307/2533837
Summary: Line transect surveys have traditionally been used only to estimate the mean intensity of an underlying spatial point process. We propose a test for complete spatial randomness and a method of estimating the clustering parameters in a simplified Neyman-Scott Poisson model, using observations collected in a line transect survey with a Gaussian detection function. These procedures use only the coordinate in the direction of the transect line. In simulation studies we compare the performance of a one-dimensional test for complete spatial randomness and a test based on the traditionally most powerful two-dimensional test. We also examine the bias and variance of the clustering parameter estimates obtained using the one-dimensional procedure. We apply the methods to data collected in a line transect survey for minke whales in the Northeastern Atlantic.
clustered populations, Neyman-Scott Poisson process, Testing in survival analysis and censored data, detection function, \(K\)-function, line transect survey, complete spatial randomness, Applications of statistics to biology and medical sciences; meta analysis
clustered populations, Neyman-Scott Poisson process, Testing in survival analysis and censored data, detection function, \(K\)-function, line transect survey, complete spatial randomness, Applications of statistics to biology and medical sciences; meta analysis
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