DS.penalty: Variance penalty due to unknown detection parameters.

In distance.sample.size: Calculates Study Size Required for Distance Sampling

Description

Calculates the variance penalty factor due to unknown detection parameters in conventional distance sampling.

Usage

DS.penalty(detection.function = c("halfnormal", "hazard"), theta,
  mean.detection.prob.value, w, P = 0, stop = F)

Arguments

detection.function	The detection function. Only "halfnormal" and "hazard" (hazard rate) are supported at present.
theta	The detection function parameters. A single value for halfnormal, or a vector of two values for hazard rate.
mean.detection.prob.value	An optional value specifying the mean detection probability over the range of observation. If this is supplied, the first element of theta should be set to NA, and theta[1] will be calculated using mean.detection.prob.value and detection.function.
w	The maximum range of observation. Objects at distance greater than w from the observer are assumed to never be recorded.
P	The proportion of the region of interest that is within w of an observer's path. P=0 may be assumed if the region is large relative to the observed area.
stop	Set to T to open a browser window (for debugging purposes)

Value

A single numeric value giving the asymptotic factor by which the variance is inflated due to unknown detection parameters.

References

Buckland S, Anderson D, Burnham K, Laake J and Borchers D (2001). Introduction to Distance Sampling: Estimating Abundance of Biological Populations. Oxford: Oxford University Press.

Clark, R. G. (2016), "Statistical efficiency in distance sampling," PLoS One, forthcoming, www.plosone.org

Examples

DS.penalty(detection.function="hazard",theta=c(NA,2),mean.detection.prob.value=0.6,w=1)

distance.sample.size documentation built on May 1, 2019, 10:27 p.m.