Derive theoretical values from known values


I am calculating CPUEs for a study.
To do this, I have a database that tracks several time variables such as the start time, the time of arrival at the target depth, the end time and a depth variable.

I have all my info to calculate my CPUE except that for some sampling we don't have the time of arrival at the target depth.
I wanted to know if it was possible to derive theoretical descent times for the missing squares from the known info (assuming that the net deployment method is respected at each sampling).

I know it doesn't just require R to work but if anyone ever knows of a package or a statistical method that would be great!

Here is an example of data :

df <- tribble(
  ~station, ~time_in, ~time_bottom, ~time_out, ~sampling_depth, 
  1, 01:40:00, 01:57:00, 02:37:04, 390, 
  2, 02:13:17, 02:31:00, 02:58:17, 250, 
  3, 06:54:08, 07:08:16, 07:47:42, 400, 
  4, 04:38:00, 04:57:39, 05:55:27, 389, 
  5, 01:17:15, NA, 02:08:36, 477, 
  6, 02:20:34, NA, 03:15:03, 278

Created on 2022-05-16 by the reprex package (v2.0.1)
Thank you

This topic was automatically closed 21 days after the last reply. New replies are no longer allowed.

If you have a query related to it or one of the replies, start a new topic and refer back with a link.