Minimal Example for Running a FIMS Model

Introduction

This vignette provides the minimal steps needed to run a Fisheries Integrated Modeling System (FIMS) model.

Setup

Load the FIMS package and clear memory:

library(FIMS)

# clear memory
clear()

Data and parameters

First, load the available data and create a FIMS data frame to create a model with. Then create a set of default parameters.

# Load sample data
data("data1")
# Prepare data for FIMS model
data_4_model <- FIMSFrame(data1)

# Define fleet specifications
fleet1 <- list(
  selectivity = list(form = "LogisticSelectivity"),
  data_distribution = c(
    Landings = "DlnormDistribution",
    AgeComp = "DmultinomDistribution",
    LengthComp = "DmultinomDistribution"
  )
)
survey1 <- list(
  selectivity = list(form = "LogisticSelectivity"),
  data_distribution = c(
    Index = "DlnormDistribution",
    AgeComp = "DmultinomDistribution",
    LengthComp = "DmultinomDistribution"
  )
)

# Create parameters
parameters <- data_4_model |>
  create_default_parameters(
    fleets = list(fleet1 = fleet1, survey1 = survey1)
  )

Initialize and Fit

Initialize the FIMS modules and fit the model.

# Run the  model with optimization
fit <- parameters |>
  initialize_fims(data = data_4_model) |>
  fit_fims(optimize = TRUE)

## ✔ Starting optimization ...
## ℹ Restarting optimizer 3 times to improve gradient.
## ℹ Maximum gradient went from 0.00539 to 0.00136 after 3 steps.
## ✔ Finished optimization
## ✔ Finished sdreport
## ℹ FIMS model version: 0.4.0
## ℹ Total run time was 5.56943 seconds
## ℹ Number of parameters: total=79, fixed_effects=79, and random_effects=0
## ℹ Maximum gradient= 0.00136
## ℹ Negative log likelihood (NLL):
## • Marginal NLL= 3230.08373
## • Total NLL= 3230.08373
## ℹ Terminal SB=

# Clear memory post-run
clear()