SizeComp


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=3.14)
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:
4.7423 (2.54-13.9615)
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=16.34) (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:
1.0244 (0.8042-1.3745)
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:
5.0688 (3.8181-7.2645)
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=7.62) (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:
1.0211 (0.8252-1.2975)
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=7.07) (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:
0.9952 (0.7139-1.4495)
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=1.61) (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:
4.5772 (3.4731-6.8001)
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=2.6) (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:
4.8665 (3.1675-8.6875)
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=3.21) (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:
0.9378 (0.7207-1.3007)
For more info, see Francis (2011).
file: comp_sizefit_data_weighting_TA1.8_LL-Survey.png