LbsprLbms class

it wraps the LIME algorithm providing a common and similar interface to other lbms methods

Value

a list with estimation and simulation results. For the latter, dataframes with the relative expected catch at length, actual catch, relative fished and un-fished populations are returned. All vectors are standarised by dividing them by their total sum.

Super class

lbmstoolbox::Lbms -> LbsprLbms

Methods

Public methods

• LbsprLbms$new()

• LbsprLbms$prepare_catch_data()

• LbsprLbms$build_lht_context()

• LbsprLbms$run()

• LbsprLbms$clone()

Inherited methods

• lbmstoolbox::Lbms$df_to_unname_matrix()
• lbmstoolbox::Lbms$transpose()

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Method new()

Initialise class.

Usage

LbsprLbms$new(biological_params, catch_data)

Arguments

biological_params

biological parameters list

catch_data

list with a long and wide catch dataframe

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Method prepare_catch_data()

Usage

LbsprLbms$prepare_catch_data(data)

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Method build_lht_context()

Usage

LbsprLbms$build_lht_context()

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Method run()

Run LBSPR algorithm

Usage

LbsprLbms$run(units = "cms", bindwidth = 1, verbose = TRUE, simul = TRUE)

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Method clone()

The objects of this class are cloneable with this method.

Usage

LbsprLbms$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.