• Version: 0.4.7.9002
• Date: 2020-11-18
• Author: Iago Mosqueira, EC JRC
• Maintainer: Iago Mosqueira [email protected]
• 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 <- 

• All release

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: [email protected]