Suppose you have the following line transect data (transect length = 1000 m). Distance in meters from the transect to the object: 6, 7, 8, 3, 2, 3, 22, 25 You want to fit an exponential detection func

Suppose you have the following line transect data (transect length = 1000 m). Distance in meters from the transect to the object: 6, 7, 8, 3, 2, 3, 22, 25 You want to fit an exponential detection function to the data. This is f(x) = (1/b)exp(−x/b).

The maximum likelihood estimator of b is mean(x) which is 9.5.

a) What is a detection function? What properties does it have?

b) Estimate the density of animals in animals per square Kilometer.

c) List as many of the assumptions of line transects as you can think of.

d) What is maximum likelihood? OR ELSE tell me what an AIC is used for.

e) Sketch the exponential curve. It is not flat near the origin, whereas the half-normal has a shoulder. What are the implications of this?

f) Why do you want to set a maximum sighting distance (truncation) in most studies?