knitr::opts_chunk$set( echo = FALSE, message = FALSE, warning = FALSE, message = FALSE, # dev = "svg", fig.width = 12, fig.height = 12 # fig.retina = 3 ) xaringanthemer::style_mono_accent( # base_color = nmfspalette::nmfs_cols("darkblue"), base_color = "#00467F", header_font_google = xaringanthemer::google_font("Josefin Sans"), text_font_google = xaringanthemer::google_font("Montserrat", "300", "300i"), code_font_google = xaringanthemer::google_font("Fira Mono"), colors = c(noaablue = "#00467F") )
class: title-slide, inverse
<style> .center2 { margin: 0; position: absolute; top: 50%; left: 50%; -ms-transform: translate(-50%, -50%); transform: translate(-50%, -50%); } </style>
.code-bg-white .remark-code, .code-bg-white .remark-code * { background-color:white!important; }
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`r table_sens("../figures/STAR_request15/sens_table_n_star.csv",
caption = "", format = "html") %>%
kableExtra::kable_styling(font_size = 12)
`
---
# 16 Request
### For the north model, provide a run in which female M is fixed at 0.3. Present model comparisons and associated informative tables/figures as in prior requests.
---
### 16 Compare time series
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---
### 16 Compare recruitment
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---
### 16 Compare likelihoods North
`r table_sens("../figures/STAR_request16/sens_table_n_star.csv",
caption = "", format = "html") %>%
kableExtra::kable_styling(font_size = 12)
`
---
# Request 17
### Provide a retrospective analysis that goes back 5 years for the northern and southern models. Report the Mohn's rho values –(Woods Hole and Alaskan/Hurtado-Ferro).
---
# Request 18
### Provide the r4ss files for the revised base models.
---
# Request 19
### For the southern model, develop the runs that would fill in a decision table based on the high and low quantiles of _M_ as inferred by the likelihood profile. Provide diagnostic outputs as appropriate.
---
# Request 20
### For the northern model, develop model runs that might encompass the different types of both observational and structural uncertainty by 1) excluding fishery dependent age data from a model and, 2) running a model with sex-specific selectivity (as in model 420) to capture the 'process' uncertainty. Include in the comparison plots and tables the model run in which _M_ is fixed at 0.3 for females.
---
### 20 Timeseries
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---
### 20 Likelihoods
`r table_sens("../figures/STAR_request20/sens_table_n_random.csv",
caption = "", format = "html", pretty = FALSE) %>%
kableExtra::kable_styling(font_size = 12)
`
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