Exact(15)
Survey proportion was held constant at 50%.
Coverage probability also varied with the level of population clustering and the survey proportion.
However, the SD of these estimates declined with increases in the survey proportion resulting in more precise estimates.
Population estimates deviated from normality when the survey proportion and detection probability were low but otherwise appeared substantially normally distributed.
The impacts of detection probability, population clustering, and survey proportion on these overall patterns are discussed in the following sections.
However, for the DO method the effect of increasing the survey proportion was most evident at intermediate detection probabilities.
Similar(45)
The DS method provided unbiased population estimates regardless of variation in population clustering, detection probabilities and survey proportions.
However, the variability of the population estimates differed substantially with detection probability for all levels of population clustering and survey proportions.
For three hypothetical populations with different levels of clustering, we generated DO and DS population size estimates for a range of detection probabilities and survey proportions.
We used computer simulations to compare population estimates based on DO and DS methods for a range of detection probabilities, survey proportions, and spatial distributions.
Population estimates for both methods were centered on the true population size for all levels of population clustering and survey proportions when detection probabilities were greater than 20%.
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