- Version: 0.4.7.9002
- Date: 2020-11-18
- Author: Iago Mosqueira, EC JRC
- Maintainer: Iago Mosqueira iago.mosqueira@ec.europa.eu
- Repository: https://github.com/iagomosqueira/ss3om/
- Bug reports: https://github.com/iagomosqueira/ss3om/issues
Tools for conditioning of Operating Models based on SS3 by considering structural uncertainty in input parameters and assumptions, jackknifing of models and use of McMC output. A grid of SS3 runs is created and results are loaded on various FLR objects using functions from the r4ss package.
- readFLIBss3 -- FLIndexBiomass
- readFLomss3 -- FLom
- readFLRPss3 -- FLpar (refpts)
- readFLSss3 -- FLStock
- readFLSRss3 -- FLSR
- readKobess3 -- data.frame (kobe)
- readRESss3 -- data.table (results)
- readRESIDss3-- FLQuants (residuals)
- readCDss3 -- lists (ctl, dat)
- readOutputss3 -- list (SS_output)
To install this package, start R and enter:
source("http://flr-project.org/R/instFLR.R")
install.packages("devtools")
devtools::install_github('r4ss/r4ss')
Sys.setenv(R_REMOTES_NO_ERRORS_FROM_WARNINGS=TRUE)
devtools::install_github('iagomosqueira/ss3om')
Provide to readFLSss3 the path to the folder containing the files. The fbar
range can be specified in the call.
her <- readFLSss3(system.file("ext-data", "herring", package="ss3om"),
range = c(minfbar = 1, maxfbar = 5))
her <- readOutputss3(system.file("ext-data", "herring", package="ss3om"))
herSSB <-
Copyright (c) 2017 European Union. Released under the European Union Public License 1.2.
You are welcome to:
- Submit suggestions and bug-reports at: https://github.com/iagomosqueira/ss3om/issues
- Send a pull request on: https://github.com/iagomosqueira/ss3om/
- Compose a friendly e-mail to: me@my.com