I am new to the ctmm R user group and creating AKDE's so apologies if my question does not make much sense, but I am trying to calculate AKDE's for multiple red deer individuals in a study area and I am running into issues with the ctmm.select() function when applied to a list of ctmm objects.
For reference my code is shown below:
SJ_Norway <- red_deer_akde %>%
filter(study_name == "Sunnfjord - Norway") %>%
select(individual.local.identifier, timestamp, location.long, location.lat)
SJ_Norway_telem <- as.telemetry(SJ_Norway) # Converting into telemetry object
m.ouf.SJ_Norway <- lapply(SJ_Norway_telem, FUN = ctmm.guess, interactive = FALSE) # Automated model guess for each ID
M.OUF.SJ_Norway <- ctmm.select(SJ_Norway_telem, m.ouf.SJ_Norway)
I can successfully obtain automated model guesses for each ID by using lapply(), and I am using ctmm.select() rather than ctmm.fit() since it can take a list of ctmm objects as an input. However, when I run ctmm.select() R produces this error:
Error in colMeans(get.telemetry(data, axes)) :
'x' must be an array of at least two dimensions
Is there anyway to calculate AKDE's for a group of individuals, rather than resorting to parsing out and calculating an AKDE for each individual?
All the help will be greatly appreciated!