Learn R Programming

multiSA

Multi-stock assessment with RTMB

multiSA (Multi-Stock Assessment with Regional Spatiotemporal dynamics) is a multi-stock, spatially-explicit age-structured model.

With explicit seasonal stock availability and movement, multiSA is intended for use in mixed fisheries where stock composition can not be readily identified in fishery data alone, i.e., from catch and age/length composition. Models can also be fitted to genetic data, e.g., stock composition of catches and close-kin pairs.

Funding for development of multiSA is provided by the NOAA Fisheries Bluefin Tuna Research Program (BTRP Grants NA23NMF4720184 and NA24NMFX472C0008-T1-01) in collaboration with the Ocean Foundation.

Atlantic bluefin tuna (Thunnus thynnus) is the first intended case study.

Installation

You can install the R package from GitHub with:

# install.packages("remotes")
remotes::install_github("Blue-Matter/multiSA")

Copy Link

Version

Install

install.packages('multiSA')

Version

0.1.0

License

GPL (>= 3)

Issues

5

Pull Requests

0

Stars

1

Forks

0

Maintainer

Quang Huynh

Last Published

February 3rd, 2026

Functions in multiSA (0.1.0)

calc_phi_project

Equilibrium spawners per recruit by projection
MSAdata-class

MSAdata S4 object
calc_POP

Predict the probability of CKMR kinship pairs
calc_phi_simple

Simple spawners per recruit calculation
calc_growth

Calculate von Bertalanffy length-at-age
conv_mov

Calculate movement matrix for all age classes
conv_selpar

Selectivity at age and length
get_sdreport

Calculate standard errors
like_CKMR

Likelihood for CKMR
calc_nextN

Project stock abundance to the next time step
posfun

Quadratic penalty function
calc_recruitment

Calculate recruitment from stock-recruit function
calc_population

Multi-fleet, multi-area, multi-stock population dynamics model
prior

Priors for MSA model
like_comp

Likelihood for composition vectors
make_parameters

Make list of parameters for RTMB
report

Generate markdown reports
profile

Profile parameters of MSA model
plot-MSA-data

Plotting functions for data in MSA model
check_data

Check dimensions and inputs in MSAdata object
plot-MSA-state

Plotting functions for fitted MSA model
conv_Sigma

Calculate covariance matrix
softmax

Softmax function
simulate

Simulate data
sapply2

sapply2 function
fit_MSA

Fit MSA model
optimize_RTMB

Optimize RTMB model
get_MSAdata

Retrieve data object used to fit model
residuals.MSAassess

Calculate model residuals
multiSA-package

multiSA: Multi-Stock Assessment
retrospective

Retrospective analysis
Dmodel-class

Dmodel S4 object
Dfishery-class

Dfishery S4 object
CondExpLt

If statements compatible with RTMB
Dlabel-class

Dlabel S4 object
AD

Additional methods for AD types
Dsurvey-class

Dsurvey S4 object
DCKMR-class

DCKMR S4 object
Dstock-class

Dstock S4 object
Dtag-class

Dtag S4 object
MSAassess-class

MSAassess S4 object
calc_eqdist

Equilibrium distribution from movement matrix
calc_index

Calculate index at age
calc_LAK

Length-at-age key
calc_F

Newton-Raphson search for fishing mortality