phuso: Carcass detection probability acording to Huso 2010

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/phuso.R

Description

Calculates carcass detection probability based on persistence time, searcher efficiency, search interval and duration of study. Persistence time obtained by any survival model (e.g. Exponential, Weibull, Log-Normal,...) can be given (but see below). Alternatively to persistence time, persistence probability can be given, In this case, the exponential model (constant persistence probability) is used to transform persistence probability into mean persistence time.
An argument shape and distribution for other than the Exponential persistence model will be provided soon.

Usage

1
phuso(s, t.bar, f, d)

Arguments

s

persistence probability: probability that a carcass remains on the study plot for one day. This parameter is only used when t.bar is not provided. Note that if s is given instead of t.bar, an exponential survival function (constant persistence probability) is used.

t.bar

mean persistence time (in days). Alternatively, s can be provided. Then, an exponential persistence model is assumed.

f

searcher efficiency: probability that a carcass present on the study plot is detected by a searcher during a seach.

d

search interval: time (in days) between two searches

Details

Time measurements (search interval) and reference time units (persistence probability) should be given in the same unit.

Value

a proportion: the probability that an animal that dies during the study period on the study plot is detected by a searcher

Author(s)

Fraenzi Korner-Nievergelt

References

Huso M (2010) An estimator of wildlife fatality from observed carcasses. Environmetrics 22: 318-329

See Also

perickson pkorner

Examples

1
phuso(s=0.8, f=0.7, d=7)

Example output

Loading required package: lme4
Loading required package: Matrix
Loading required package: survival
[1] 0.3541598

carcass documentation built on May 2, 2019, 2:42 a.m.