Performance Metric
10 August, 2021
Required packages
To follow this tutorial you should have installed the following packages:
- CRAN:
- FLR: FLCore
You can do so as follows:
install.packages(c("iterators"))
install.packages(c("FLCore"), repos="http://flr-project.org/R")library(devtools)
install_github("lauriekell/FLCandy")Section
library(plyr)
library(reshape)
library(randtests)library(FLCore)
library(FLBRP)
library(FLasher)
library(ggplotFL)library(FLCandy)
library(mydas)
library(FLife) data("ple4")
data("ple4brp")om=fwdWindow(ple4,end=2050,ple4brp)
deviates=rlnoise(100,rec(om)%=%1,0.3,0.7)
om=propagate(om,100)
om.msy=fwd(om,fbar=fbar(om)[,ac(2018:2050)]%=%c(refpts(ple4brp)["msy","harvest"]),sr=ple4brp,residuals=deviates)
om.f01=fwd(om,fbar=fbar(om)[,ac(2018:2050)]%=%c(refpts(ple4brp)["f0.1","harvest"]),sr=ple4brp,residuals=deviates)
om.mey=fwd(om,fbar=fbar(om)[,ac(2018:2050)]%=%c(refpts(ple4brp)["mey","harvest"]),sr=ple4brp,residuals=deviates)oms=FLStocks("MSY" =om.msy,
"F0.1"=om.f01,
"MEY" =om.mey)
plot(oms)
stats=ldply(oms,function(x) omSmry(x,ple4brp))
head(stats)| .id | iter | year | ssb | stock | rec | catch | catchjuv | fbar | swt | cwt | sage | cage | crash_harvest | virgin_rec | virgin_ssb | msy_harvest | msy_ssb | msy_yield | msy_biomass | rec_hat |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| MSY | 1 | 1957 | 342223.2 | 402414.2 | 477074 | 78360.36 | 11791.67 | 0.2416816 | 0.2298036 | 0.2607206 | 3.370112 | 3.796387 | 0.5251667 | 508719.8 | 1738829 | 0.2753625 | 732514.9 | 82011.12 | 831613 | 5.197113 |
| MSY | 1 | 1958 | 355374.8 | 421111.4 | 710748 | 88785.20 | 12109.60 | 0.2786560 | 0.2095089 | 0.2465510 | 3.092674 | 3.585479 | 0.5251667 | 508719.8 | 1738829 | 0.2753625 | 732514.9 | 82011.12 | 831613 | 5.197113 |
| MSY | 1 | 1959 | 362119.4 | 456662.1 | 874712 | 105186.13 | 20053.53 | 0.3108412 | 0.1941832 | 0.2336876 | 2.848103 | 3.269446 | 0.5251667 | 508719.8 | 1738829 | 0.2753625 | 732514.9 | 82011.12 | 831613 | 5.197113 |
| MSY | 1 | 1960 | 380052.2 | 485669.6 | 797702 | 117974.54 | 25053.53 | 0.3244846 | 0.1943812 | 0.2297833 | 2.844621 | 3.144671 | 0.5251667 | 508719.8 | 1738829 | 0.2753625 | 732514.9 | 82011.12 | 831613 | 5.197113 |
| MSY | 1 | 1961 | 391385.5 | 499319.2 | 870799 | 119540.66 | 23842.19 | 0.3251898 | 0.1888139 | 0.2210918 | 2.831387 | 3.130246 | 0.5251667 | 508719.8 | 1738829 | 0.2753625 | 732514.9 | 82011.12 | 831613 | 5.197113 |
| MSY | 1 | 1962 | 482245.1 | 575609.4 | 615691 | 126290.43 | 21856.52 | 0.3355884 | 0.2306490 | 0.2352572 | 3.049737 | 3.332219 | 0.5251667 | 508719.8 | 1738829 | 0.2753625 | 732514.9 | 82011.12 | 831613 | 5.197113 |
pMetrics=ddply(stats, .(.id), mydas:::smryStat)
pMetrics| .id | safety | blim | plim | ftar | btar | kobe.year | kobe.n | yield | yieldAav | yieldAav2 | yieldAav3 | yieldRnd | ssbRnd | fbRnd |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| F0.1 | 1.02e-05 | 0.4906060 | 0.6489362 | 0.5640401 | 0.2776612 | 2014 | 3600 | 1.898936 | 0.0756037 | 0.1338450 | 0.1788343 | 0 | 0 | 1.2e-05 |
| MEY | 1.02e-05 | 0.4158399 | 0.6489362 | 0.7133332 | 0.2776612 | 2014 | 3600 | 2.250383 | 0.0774168 | 0.1390430 | 0.1881190 | 0 | 0 | 9.8e-06 |
| MSY | 1.02e-05 | 0.4068393 | 0.6489362 | 0.7133332 | 0.2776612 | 2014 | 300 | 2.290422 | 0.0779797 | 0.1401134 | 0.1897251 | 0 | 0 | 9.8e-06 |
Subsection
Nam dignissim vulputate ante sit amet mollis. Donec hendrerit eros vel ligula malesuada consectetur. Morbi porta placerat mi, a feugiat ipsum placerat nec. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Vestibulum at elementum magna, at venenatis augue. Pellentesque mattis, nisi vel lacinia luctus, sem leo faucibus elit, et gravida eros mi ac nisl. Morbi pellentesque molestie placerat. Nullam quis condimentum mauris. Donec vitae accumsan eros. Proin sed tincidunt mauris. Mauris lobortis commodo tellus, et fringilla lorem euismod et. Vestibulum a purus luctus, consequat massa non, bibendum ligula. Nam at lorem nulla. Curabitur non augue consectetur, molestie dolor vel, dignissim mi.
More information
To learn more about this subsection, check the FLPKG.
References
L. T. Kell, I. Mosqueira, P. Grosjean, J-M. Fromentin, D. Garcia, R. Hillary, E. Jardim, S. Mardle, M. A. Pastoors, J. J. Poos, F. Scott, R. D. Scott; FLR: an open-source framework for the evaluation and development of management strategies. ICES J Mar Sci 2007; 64 (4): 640-646. doi: 10.1093/icesjms/fsm012.
More information
- You can submit bug reports, questions or suggestions on this tutorial at https://github.com/flr/doc/issues.
- Alternatively, send a pull request to https://github.com/flr/doc/.
- For more information on the FLR Project for Quantitative Fisheries Science in R, visit the FLR webpage: http://flr-project.org.
Software Versions
- R version 4.0.3 (2020-10-10)
- FLCore: 2.6.16.9002
- Compiled: Tue Aug 10 11:43:24 2021
License
This document is licensed under the Creative Commons Attribution-ShareAlike 4.0 International license.