Mark-resight model with varying effort?
Posted: Wed May 23, 2018 9:45 pm
Hi All,
I'm wanting a fit a mark-resight model where lamda_j = E_j*lamda, where E_j is the effort expended for either group j or primary period j (if using a robust design). For example, E_j might be the number of days of searching in different areas, or days searching each primary period. In a GLM framework, E_j would often be referred to as an 'offset'.
I've had a poke around various websites and documentation and can't find a way to do this easily. Which now that I've said that, someone is going to post a link and tell me to RTFM
I could use E_j as a covariate, which kind of does what I want but not exactly. Only other solution I can think of is breaking data down into periods of consistently-sized effort, and use robust design with appropriate constraints and missing data.
Ideally looking for a solution in RMark/Mark, but open to suggestions of other R-based solutions.
Cheers
Darryl
I'm wanting a fit a mark-resight model where lamda_j = E_j*lamda, where E_j is the effort expended for either group j or primary period j (if using a robust design). For example, E_j might be the number of days of searching in different areas, or days searching each primary period. In a GLM framework, E_j would often be referred to as an 'offset'.
I've had a poke around various websites and documentation and can't find a way to do this easily. Which now that I've said that, someone is going to post a link and tell me to RTFM
I could use E_j as a covariate, which kind of does what I want but not exactly. Only other solution I can think of is breaking data down into periods of consistently-sized effort, and use robust design with appropriate constraints and missing data.
Ideally looking for a solution in RMark/Mark, but open to suggestions of other R-based solutions.
Cheers
Darryl