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=3.05)
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:
4.765 (2.4785-13.4117)
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=16.14) (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:
1.0332 (0.8042-1.4054)
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=1.59) (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:
4.9265 (3.7301-7.1654)
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=7.57) (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:
1.0244 (0.8461-1.3121)
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=7.11) (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:
0.9902 (0.7352-1.4399)
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=1.58) (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:
4.366 (3.2371-6.3095)
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=2.63) (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:
4.8234 (3.0052-8.5548)
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=3.26) (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:
0.8978 (0.695-1.2375)
For more info, see Francis (2011).
file: comp_sizefit_data_weighting_TA1.8_LL-Survey.png