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it generates two dataframes containing information about the estimated vs real catch as well as the estimated unfished vs fished population. It does not apply any depletion threshold for the unfished population.

Value

A list of dataframes with the expected catch and fished/unfished population

a dataframe with the real standarised relative real and standarised expected catch

a dataframe with the unfished and fished population

Public fields

catch_data

list of long and wide dataframes

mid_points

vector of modelled lengths by LIME

ages

integer vector

estimated_catch

estimated catch three-dimensional matrix

fished_population

estimated fished population matrix

fished_population

estimated fished population matrix

unfished_population

estimated unfished population matrix

Methods


Method new()

Initialise the class

Usage

LimeSimulation$new(
  catch_data,
  mid_points,
  ages,
  estimated_catch,
  fished_population,
  unfished_population
)

Arguments

catch_data

list of long and wide dataframes

mid_points

vector of modelled lengths by LIME

estimated_catch

estimated catch three-dimensional matrix

fished_population

estimated fished population matrix

fished_population

estimated fished population matrix


Method run()

Generates the model fitting information (relative catch at length and relative fished and unfished population at age)

Usage

LimeSimulation$run()


Method build_catch_df()

Builds a catch dataframe with the relative and expected catch. Both data are standarised (divided by their total sum)

Usage

LimeSimulation$build_catch_df()


Method build_population_df()

Builds a population dataframe with expected unfished and fished population. Both data are standarised (divided by their total sum). The expected values are relative to age rather than length.

Usage

LimeSimulation$build_population_df()


Method clone()

The objects of this class are cloneable with this method.

Usage

LimeSimulation$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.