mark-resight experiment

[garciap]

Dear all,

I am using mark-resight models in MARK, particularly in my case the so-called Poisson log-normal. While analisying my data I have two doubts. One of it I think it is solved, but not the another one.

The first, I think now is fine. I am not sure of how many of the animals marked are currently in my area. In the two ending lines "Known Mark Group=1", should I write 0 in any occasion (as I do not know the number of marked animals present)? or should I post the minimum number marked I know to be present?

Well, and the second one, MARK "A Gentle Introductiion" chapter indicates that it is possible to derive a parameter, the lambda as a function of another two variables. Nevertheless, I am not able to find the equation to do that, does anyone know how to do this?

Best regards

Pablo

[bmcclintock]

Hi Pablo,

1) For any occasion during which the number of marks is unknown, one needs to include '0' under 'Known Marks' for that occasion. If the number of marks is known exactly for any occasion, then the exact number is included under 'Known Marks' for that occasion. See pages 18 - 18 to 18-32 in 'The Book'. For example, suppose in a 3-year study the number of marks was known exactly in the first year (say there were n = 52 marked individuals in the first year), but not in the second or third years. Regardless of the minimum number of marks known to be present in the second and third years, the entry under 'Known Marks' would be:

Known Marks Group=1;
52 0 0;

2) In MARK, derived parameters are obtained by clicking on the fifth button (from the left) of the results browser. The actual equations for the derived parameters can be found in the mark-resight papers cited in 'The Book'.

Cheers,
Brett