detection: Detection function

In maudqueroue/intercali: Intercalibration Des Différents Types De Suivis Aeriens

Detection function

Description

This funtion allows simulating the probability that a individual could be observed according to the sample design. The detection function could be an uniform detection function with a probability of detection g_zero on the whole strip band until the maximum distance of observation (in m) truncation_m. The detection function could also be a half normal detection function for which we can choose the effective strip width (in km) esw_km i.e. the distance at which there are as much non detected individuals before this distance than detected individuals after this distance. For the half normal detection function it is also possible to choose the proability of detection at 0 meter g_zero and the maximum distance of observation (in m) truncation_m.

Usage

detection(dist_obj, key, esw_km = NA, g_zero = NA, truncation_m)

Arguments

dist_obj	dataframe. Contains each observation and the distance between the observation and the transects/segments.
key	character. Form of the detection function "hn" or "unif".
esw_km	numeric. Effective strip width (in km). This argument is needed only for the 'hn' form. By default NA.
g_zero	numeric. The detection probability for the 'unif' form. By default NA.
truncation_m	numeric. A single numeric value (in m) describing the longest distance at which an object may be observed.

Value

dataframe. The dist dataframe with new columns : "proba" (numeric values between 0 and 1), the probability of being detection and 'detected' (0 or 1)informing if the individual is detected by the sample design.

Examples

library(ggplot2)

data(dataset_dist)

detected <- detection(dist_obj = dataset_dist,
                   key = "hn",
                   esw_km = 0.16,
                   g_zero = 1,
                   truncation_m = 400)

ggplot(detected, aes(x=distance_m, y=proba)) +
  geom_point(color = "indianred4") +
  xlim(0,500)


detected <- detection(dist_obj = dataset_dist,
                   key = "unif",
                   g_zero = 0.8,
                   truncation_m = 250) 

ggplot(detected, aes(x=distance_m, y=proba)) +
  geom_point(color = "indianred4") +
  xlim(0,500)

maudqueroue/intercali documentation built on Oct. 8, 2022, 2:09 p.m.