Probability of detecting a feature that covers a proportion theta of the survey area.

Share:

Description

The function can calculate the probability of a feature that occupies a proportion theta of the sampling area and where the sampling point density of the survey is specified; the sampling point density needed to achieve a specified probability of detection, where theta is also specified ; or the value of theta that will be detected with specified probability and sampling density.Unless the feature is made of a large number of random segments (see below for how to deal with this situation), these methods apply only when the pattern of points in the sampling deisgn is random.

Usage

1
detect.prop(statistic, theta=NA, pdetect=NA, ssize=NA)

Arguments

statistic

Describes what aspect of design you want calculated. The choices are "P" (probability detection); "N" (sample size) or "F" (feature proportion).

theta

Feature proportion. Not needed if statistic="F".

pdetect

Probability detection. Not needed if statistic="P".

ssize

Sample size. Not needed if statistic="N".

Details

The probability of detection is p = 1 - (1 - theta)^{N}. Formulae for theta and N are readily obtained from this formula. If the spatial pattern of the feature consists of lots of small, random uniformly distributed fragments, then we can redefine theta = Na/A where a is the area of the sampling unit and A is the sampling area.In this situation, the probability of patch detection applies no matter what the spatial pattern of points in the sampling design. Unlike detect, detect.prop works for vectors - so long as the input vectors are of the same length.

Value

prob

Probability of detection

ssize

Sample size

prop

Feature proportion

Author(s)

Jon Barry: Jon.Barry@cefas.co.uk

Examples

1
2
3
detect.prop(statistic='P', theta=0.02, ssize=80)
detect.prop(statistic='N', theta=0.02, pdetect=0.9)
detect.prop(statistic='F', pdetect=0.9, ssize=80)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.