Size comps, aggregated across time by fleet.
Labels 'retained' and 'discard' indicate discarded or retained sampled for each fleet. Panels without this designation represent the whole catch.
file: comp_sizefit__aggregated_across_time.png
Size comps, whole catch, LL-n-A1.
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method.
file: comp_sizefit_flt1mkt0.png
Pearson residuals, whole catch, LL-n-A1 (max=3.44)
Closed bubbles are positive residuals (observed > expected) and open bubbles are negative residuals (observed < expected).
file: comp_sizefit_residsflt1mkt0.png
N-EffN comparison, Size comps, whole catch, LL-n-A1
file: comp_sizefit_sampsize_flt1mkt0.png
Mean size for LL-n-A1 with 95% confidence intervals based on current sample sizes.
Francis data weighting method TA1.8: thinner intervals (with capped ends) show result of further adjusting sample sizes based on suggested multiplier (with 95% interval) for size data from LL-n-A1:
4.6216 (2.354-13.7748)
For more info, see Francis (2011).
file: comp_sizefit_data_weighting_TA1.8_LL-n-A1.png
Size comps, whole catch, LL-n-A2 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method.
file: comp_sizefit_flt2mkt0_page1.png
Size comps, whole catch, LL-n-A2 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 5)
file: comp_sizefit_flt2mkt0_page2.png
Size comps, whole catch, LL-n-A2 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 5) (plot 3 of 5)
file: comp_sizefit_flt2mkt0_page3.png
Size comps, whole catch, LL-n-A2 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 5) (plot 3 of 5) (plot 4 of 5)
file: comp_sizefit_flt2mkt0_page4.png
Size comps, whole catch, LL-n-A2 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 5) (plot 3 of 5) (plot 4 of 5) (plot 5 of 5)
file: comp_sizefit_flt2mkt0_page5.png
Pearson residuals, whole catch, LL-n-A2 (max=17.32) (plot 5 of 5)
Closed bubbles are positive residuals (observed > expected) and open bubbles are negative residuals (observed < expected).
file: comp_sizefit_residsflt2mkt0_page5.png
N-EffN comparison, Size comps, whole catch, LL-n-A2
file: comp_sizefit_sampsize_flt2mkt0.png
Mean size for LL-n-A2 with 95% confidence intervals based on current sample sizes.
Francis data weighting method TA1.8: thinner intervals (with capped ends) show result of further adjusting sample sizes based on suggested multiplier (with 95% interval) for size data from LL-n-A2:
1.0197 (0.7953-1.3646)
For more info, see Francis (2011).
file: comp_sizefit_data_weighting_TA1.8_LL-n-A2.png
Size comps, whole catch, LL-n-A3 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method.
file: comp_sizefit_flt3mkt0_page1.png
Size comps, whole catch, LL-n-A3 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 5)
file: comp_sizefit_flt3mkt0_page2.png
Size comps, whole catch, LL-n-A3 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 5) (plot 3 of 5)
file: comp_sizefit_flt3mkt0_page3.png
Size comps, whole catch, LL-n-A3 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 5) (plot 3 of 5) (plot 4 of 5)
file: comp_sizefit_flt3mkt0_page4.png
Size comps, whole catch, LL-n-A3 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 5) (plot 3 of 5) (plot 4 of 5) (plot 5 of 5)
file: comp_sizefit_flt3mkt0_page5.png
Pearson residuals, whole catch, LL-n-A3 (max=1.56) (plot 5 of 5)
Closed bubbles are positive residuals (observed > expected) and open bubbles are negative residuals (observed < expected).
file: comp_sizefit_residsflt3mkt0_page5.png
N-EffN comparison, Size comps, whole catch, LL-n-A3
file: comp_sizefit_sampsize_flt3mkt0.png
Mean size for LL-n-A3 with 95% confidence intervals based on current sample sizes.
Francis data weighting method TA1.8: thinner intervals (with capped ends) show result of further adjusting sample sizes based on suggested multiplier (with 95% interval) for size data from LL-n-A3:
4.9517 (3.7842-6.9936)
For more info, see Francis (2011).
file: comp_sizefit_data_weighting_TA1.8_LL-n-A3.png
Size comps, whole catch, LL-n-A4 (plot 1 of 6).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method.
file: comp_sizefit_flt4mkt0_page1.png
Size comps, whole catch, LL-n-A4 (plot 1 of 6).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 6)
file: comp_sizefit_flt4mkt0_page2.png
Size comps, whole catch, LL-n-A4 (plot 1 of 6).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 6) (plot 3 of 6)
file: comp_sizefit_flt4mkt0_page3.png
Size comps, whole catch, LL-n-A4 (plot 1 of 6).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 6) (plot 3 of 6) (plot 4 of 6)
file: comp_sizefit_flt4mkt0_page4.png
Size comps, whole catch, LL-n-A4 (plot 1 of 6).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 6) (plot 3 of 6) (plot 4 of 6) (plot 5 of 6)
file: comp_sizefit_flt4mkt0_page5.png
Size comps, whole catch, LL-n-A4 (plot 1 of 6).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 6) (plot 3 of 6) (plot 4 of 6) (plot 5 of 6) (plot 6 of 6)
file: comp_sizefit_flt4mkt0_page6.png
Pearson residuals, whole catch, LL-n-A4 (max=8.38) (plot 6 of 6)
Closed bubbles are positive residuals (observed > expected) and open bubbles are negative residuals (observed < expected).
file: comp_sizefit_residsflt4mkt0_page6.png
N-EffN comparison, Size comps, whole catch, LL-n-A4
file: comp_sizefit_sampsize_flt4mkt0.png
Mean size for LL-n-A4 with 95% confidence intervals based on current sample sizes.
Francis data weighting method TA1.8: thinner intervals (with capped ends) show result of further adjusting sample sizes based on suggested multiplier (with 95% interval) for size data from LL-n-A4:
0.9934 (0.8312-1.277)
For more info, see Francis (2011).
file: comp_sizefit_data_weighting_TA1.8_LL-n-A4.png
Size comps, whole catch, LL-n-A5 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method.
file: comp_sizefit_flt5mkt0_page1.png
Size comps, whole catch, LL-n-A5 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 5)
file: comp_sizefit_flt5mkt0_page2.png
Size comps, whole catch, LL-n-A5 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 5) (plot 3 of 5)
file: comp_sizefit_flt5mkt0_page3.png
Size comps, whole catch, LL-n-A5 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 5) (plot 3 of 5) (plot 4 of 5)
file: comp_sizefit_flt5mkt0_page4.png
Size comps, whole catch, LL-n-A5 (plot 1 of 5).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 5) (plot 3 of 5) (plot 4 of 5) (plot 5 of 5)
file: comp_sizefit_flt5mkt0_page5.png
Pearson residuals, whole catch, LL-n-A5 (max=7.65) (plot 5 of 5)
Closed bubbles are positive residuals (observed > expected) and open bubbles are negative residuals (observed < expected).
file: comp_sizefit_residsflt5mkt0_page5.png
N-EffN comparison, Size comps, whole catch, LL-n-A5
file: comp_sizefit_sampsize_flt5mkt0.png
Mean size for LL-n-A5 with 95% confidence intervals based on current sample sizes.
Francis data weighting method TA1.8: thinner intervals (with capped ends) show result of further adjusting sample sizes based on suggested multiplier (with 95% interval) for size data from LL-n-A5:
1.0045 (0.7354-1.4924)
For more info, see Francis (2011).
file: comp_sizefit_data_weighting_TA1.8_LL-n-A5.png
Size comps, whole catch, LL-n-A6 (plot 1 of 4).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method.
file: comp_sizefit_flt6mkt0_page1.png
Size comps, whole catch, LL-n-A6 (plot 1 of 4).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 4)
file: comp_sizefit_flt6mkt0_page2.png
Size comps, whole catch, LL-n-A6 (plot 1 of 4).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 4) (plot 3 of 4)
file: comp_sizefit_flt6mkt0_page3.png
Size comps, whole catch, LL-n-A6 (plot 1 of 4).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 4) (plot 3 of 4) (plot 4 of 4)
file: comp_sizefit_flt6mkt0_page4.png
Pearson residuals, whole catch, LL-n-A6 (max=1.49) (plot 4 of 4)
Closed bubbles are positive residuals (observed > expected) and open bubbles are negative residuals (observed < expected).
file: comp_sizefit_residsflt6mkt0_page4.png
N-EffN comparison, Size comps, whole catch, LL-n-A6
file: comp_sizefit_sampsize_flt6mkt0.png
Mean size for LL-n-A6 with 95% confidence intervals based on current sample sizes.
Francis data weighting method TA1.8: thinner intervals (with capped ends) show result of further adjusting sample sizes based on suggested multiplier (with 95% interval) for size data from LL-n-A6:
5.1351 (3.7767-7.4364)
For more info, see Francis (2011).
file: comp_sizefit_data_weighting_TA1.8_LL-n-A6.png
Size comps, whole catch, LL-n-A7 (plot 1 of 3).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method.
file: comp_sizefit_flt7mkt0_page1.png
Size comps, whole catch, LL-n-A7 (plot 1 of 3).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 3)
file: comp_sizefit_flt7mkt0_page2.png
Size comps, whole catch, LL-n-A7 (plot 1 of 3).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 3) (plot 3 of 3)
file: comp_sizefit_flt7mkt0_page3.png
Pearson residuals, whole catch, LL-n-A7 (max=2.73) (plot 3 of 3)
Closed bubbles are positive residuals (observed > expected) and open bubbles are negative residuals (observed < expected).
file: comp_sizefit_residsflt7mkt0_page3.png
N-EffN comparison, Size comps, whole catch, LL-n-A7
file: comp_sizefit_sampsize_flt7mkt0.png
Mean size for LL-n-A7 with 95% confidence intervals based on current sample sizes.
Francis data weighting method TA1.8: thinner intervals (with capped ends) show result of further adjusting sample sizes based on suggested multiplier (with 95% interval) for size data from LL-n-A7:
5.1791 (3.3345-8.9408)
For more info, see Francis (2011).
file: comp_sizefit_data_weighting_TA1.8_LL-n-A7.png
Size comps, whole catch, LL-Survey (plot 1 of 4).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method.
file: comp_sizefit_flt23mkt0_page1.png
Size comps, whole catch, LL-Survey (plot 1 of 4).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 4)
file: comp_sizefit_flt23mkt0_page2.png
Size comps, whole catch, LL-Survey (plot 1 of 4).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 4) (plot 3 of 4)
file: comp_sizefit_flt23mkt0_page3.png
Size comps, whole catch, LL-Survey (plot 1 of 4).
'N adj.' is the input sample size after data-weighting adjustment. N eff. is the calculated effective sample size used in the McAllister-Ianelli tuning method. (plot 2 of 4) (plot 3 of 4) (plot 4 of 4)
file: comp_sizefit_flt23mkt0_page4.png
Pearson residuals, whole catch, LL-Survey (max=2.82) (plot 4 of 4)
Closed bubbles are positive residuals (observed > expected) and open bubbles are negative residuals (observed < expected).
file: comp_sizefit_residsflt23mkt0_page4.png
N-EffN comparison, Size comps, whole catch, LL-Survey
file: comp_sizefit_sampsize_flt23mkt0.png
Mean size for LL-Survey with 95% confidence intervals based on current sample sizes.
Francis data weighting method TA1.8: thinner intervals (with capped ends) show result of further adjusting sample sizes based on suggested multiplier (with 95% interval) for size data from LL-Survey:
0.9909 (0.7517-1.4241)
For more info, see Francis (2011).
file: comp_sizefit_data_weighting_TA1.8_LL-Survey.png