1 / 9

Petrale STAR Day 2 Requests

Petrale STAR Day 2 Requests. 1. Increase input standard error for commercial log CPUE. Make the standard error is about the same as the standard error for the NWFSC survey log index. Do an SS3 run with extra standard error estimated, but with a lower bound of zero on the extra standard error.

isanne
Download Presentation

Petrale STAR Day 2 Requests

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Petrale STAR Day 2 Requests

  2. 1. Increase input standard error for commercial log CPUE. Make the standard error is about the same as the standard error for the NWFSC survey log index. Do an SS3 run with extra standard error estimated, but with a lower bound of zero on the extra standard error.

  3. 1. Increase input standard error for commercial log CPUE. Make the standard error is about the same as the standard error for the NWFSC survey log index. Do an SS3 run with extra standard error estimated, but with a lower bound of zero on the extra standard error.

  4. 2. Change CPUE catchability model to include an unconstrained random walk in q since trip limits were implemented (since 2006)

  5. 2. Change CPUE catchability model to include an unconstrained random walk in q since trip limits were implemented (since 2006)

  6. 2. Change CPUE catchability model to include an unconstrained random walk in q since trip limits were implemented (since 2006)

  7. 3. Axis of uncertainty should include a range of M values derived from the likelihood profile. Make sure the range of M is wide enough to capture 1.2 log likelihood units. Verify how this range compares to interval based on asymptotic normal approximation with hessian-based standard error.

  8. 4. Profile full suite of output for new base case. Go to r4SS outputs

  9. 3. Axis of uncertainty should include a range of M values derived from the likelihood profile. Make sure the range of M is wide enough to capture 1.2 log likelihood units. Verify how this range compares to interval based on asymptotic normal approximation with hessian-based standard error.

More Related