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Create default parameters for a FIMS model

Source: R/create_default_parameters.R
create_default_parameters.Rd

This function generates a Fisheries Integrated Modeling System (FIMS) model configuration with detailed parameter specifications. This function takes a high-level configuration tibble and generates the corresponding parameters with default initial values and estimation settings required to build and run the model.

Usage

create_default_parameters(configurations, data)

Arguments

configurations

A tibble of model configurations. Typically created by create_default_configurations(). Users can modify this tibble to customize the model structure before generating default parameters.

data

An S4 object. FIMS input data.

Value

A tibble with default model parameters. The tibble has a nested structure with the following top-level columns.

model_family:

The specified model family (e.g., "catch_at_age").

module_name:

The name of the FIMS module (e.g., "Data", "Selectivity", "Recruitment", "Growth", "Maturity").

fleet_name:

The name of the fleet the module applies to. This will be NA for non-fleet-specific modules like "Recruitment".

data:

A list-column containing a tibble with detailed parameters. Unnesting this column reveals:

module_type:

The specific type of the module (e.g., "Logistic" for a "Selectivity" module).

label:

The name of the parameter (e.g., "inflection_point").

distribution_link:

The component the distribution module links to.

age:

The age the parameter applies to.

length:

The length bin the parameter applies to.

time:

The time step (i.e., year) the parameter applies to.

value:

The initial value of the parameter.

estimation_type:

The type of estimation (e.g., "constant", "fixed_effects", "random_effects").

distribution_type:

The type of distribution (e.g., "Data", "process").

distribution:

The name of distribution (e.g., "Dlnorm", Dmultinom).

Details

The function processes the input configurations tibble, which defines the modules for different model components (e.g., "Selectivity", "Recruitment"). For each module specified, it calls internal helper functions to create a default set of parameters. For example, if a fleet's selectivity is configured as "Logistic", it generates initial values for "inflection_point" and "slope".

See also

Examples

if (FALSE) { # \dontrun{
# Load the example dataset and create a FIMS data frame
data("data1")
fims_frame <- FIMSFrame(data1)

# Create default configurations
default_configurations <- create_default_configurations(fims_frame)

# Create default parameters
default_parameters <- create_default_parameters(
  configurations = default_configurations,
  data = fims_frame
) |>
  tidyr::unnest(cols = data)

# Update selectivity parameters for survey1
updated_parameters <- default_parameters |>
  dplyr::rows_update(
    tibble::tibble(
      fleet_name = "survey1",
      label = c("inflection_point", "slope"),
      value = c(1.5, 2)
    ),
    by = c("fleet_name", "label")
  )

# Do the same as above except, model fleet1 with double logistic selectivity
# To see required parameters for double logistic selectivity, run
# show(DoubleLogisticSelectivity)
parameters_with_double_logistic <- default_configurations |>
  tidyr::unnest(cols = data) |>
  dplyr::rows_update(
    tibble::tibble(
      module_name = "Selectivity",
      fleet_name = "fleet1",
      module_type = "DoubleLogistic"
    ),
    by = c("module_name", "fleet_name")
  ) |>
  create_default_parameters(
    data = fims_frame
  )
} # }