distance.sample.size: Required study size in distance sampling.

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

Description

Calculates the study size needed to achieve a target coefficient of variation for the abundance estimator in conventional distance sampling.

Usage

distance.sample.size(cv.pct, N = Inf, overdispersion = 2,
  detection.function, theta, mean.detection.prob.value,
  shape.hazard = c("verynarrow", "narrow", "wide"), w, pilot.cv.pct, pilot.N,
  pilot.P, pilot.detections, pilot.theta, pilot.w = pilot.w,
  pilot.detection.function, stop = F)

Arguments

cv.pct	The required cv expressed as a percentage. For example, use cv=15 for a coefficient of variation of 15%.
N	Optional. The total abundance of the objects or animals of interest in the whole region of interest. In practice may not be known, in which either a rough estimate can be used, or N can be set to infinity (the default) which is equivalent to assuming that the fraction of all animals observed is small. Setting N to Inf results in an over-estimation (usually slight) of the required sample size.
overdispersion	The factor by which the variance of the number of objects observed is inflated due to overdispersion. Burnham, Anderson and Laake (1985) suggest that a value of 2 may be fairly typical in practice.
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.
shape.hazard	Can be used to specify theta according to 3 preset hazard rate models (the ones used in the simulation in Clark 2016). If shape.hazard is supplied, detection.function should be "hazard", theta need not be supplied, and w need not be supplied as is set to 1 (results in detection probabilities of 0.1 to 0.15 at w). All three options have an average detection rate of 0.6.
w	The maximum range of observation. Objects at distance greater than w from the observer are assumed to never be recorded.
pilot.cv.pct	Optional. The CV achieved by a pilot study. Assumed to allow for the sampling fraction used, the variability due to unknown theta, and overdispersion. If supplied, pilot.detections and pilot.theta must also be provided. If pilot information is provided, it is used to estimate overdispersion (if overdispersion is missing)
pilot.N	Optional. The estimated abundance from the pilot study. Used to estimate overdispersion (if missing).
pilot.P	Optional. The proportion of the area of the region observable in the pilot study. Used to estimate overdispersion (if missing). If not supplied, it is inferred from the other pilot information.
pilot.detections	Optional. The number of detections from the pilot study. Used to estimate overdispersion (if missing).
pilot.theta	Optional. The estimated detection parameter/s from the pilot study.
pilot.w	Optional. The maximum range of observation in the pilot study. If missing, defaults to w.
pilot.detection.function	Optional. The detection function used for the pilot study. Only "halfnormal" and "hazard" (hazard rate) are supported at present. If not supplied, defaults to detection.function.
stop	Set to T to open a browser window (for debugging purposes)

Details

It may be impossible to achieve the target precision, even if the expected sample size is equal to its maximum possible value of N divided by the mean detection probability. In this case, missing values are returned for the required sample size and coverage proportion, and a warning is issued.

Value

A vector with named values giving: the required expected sample size, the required coverage rate (i.e. the proportion P of the region falling within distance w of an observer's path), the penalty due to unknown detection parameters when P<<1, and the penalty due to unknown detection parameters for the required value of P. The user can then use either the required coverage rate to determine how closely to space transect lines (or how many points to select in a point transect study)

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.

Burnham KP, Anderson DR, Laake JL (1985), "Efficiency and bias in strip and line transect sampling". The Journal of Wildlife Management, pp. 1012-1018.

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

Examples

distance.sample.size(cv.pct=15,N=1000,detection.function="hazard",shape.hazard="narrow")
distance.sample.size(cv.pct=15,N=1000,detection.function="halfnormal",theta=90,w=200,
pilot.N=200,pilot.cv.pct=20,pilot.theta=90,pilot.w=200,
pilot.detection.function="halfnormal",pilot.detections=63)

rgcstats/distance.sample.size documentation built on May 27, 2019, 7:22 a.m.