Dummymrdsobjects

Justification

It might be the case that you have a list of detection probabilities for your observations (say from some detection function fitting process other than Distance or mrds). In that case it would be nice to use them with dsm.

These instructions detail how one can use these detection probabilities (and some other information) to build a "dummy" object to give to dsm.

What you need

You'll need to have the following data loaded into R to build the dummy object:

• truncation distance
• left truncation (if you're using one)
• vector of probabilities
• unique object identifier for each probabilities (these need to match what you have in your observation data.frame)

How to do it

dsm expects a ddf object, which is a list with a bunch of elements in it. We only need re-create the elements of the list that dsm cares about.

Let's call our dummy object ddf.dummy and initialize it as a list:

ddf.dummy <- list()

ddf.dummy$meta.data <- list()
ddf.dummy$meta.data$width <- 350
ddf.dummy$meta.data$left <- 22

ddf.dummy$fitted <- bl.prob$pdot.mew

names(ddf.dummy$fitted) <- bl.prob$object