DynState.control: 2 species quota dynamic state variable model

In flr/FLRDynState: 2 spec Dynamic State Variable Model

Description

The DynState.control function simulates decision and outcomes in a 2 species mixed fisheries under Individual Tradeable Quota constraints or effort constraints. The simulation technique used is called dynamic state variable modelling (Clark and Mangel,2000). The input to the model is defined by two DynStateInput objects.

Usage

	DynState.control(Spp1Uplimit, Spp2Uplimit, EffortUplimit, SimNumber, Spp1Price, Spp2Price, EffortPrice, Spp1Increment, Spp2Increment, AddNoFishing, Spp1DiscardSteps, Spp2DiscardSteps, RIStar, ChoiceDist)

Arguments

Spp1Uplimit	The species 1 quota
Spp2Uplimit	The species 2 quota
EffortUplimit	the effort quota
SimNumber	The number of forward simulations
Spp1Price	The price of one unit of species 1
Spp2Price	The price of one unit of species 2
EffortPrice	the cost of one unit of effort
Increments	the number of bins for discretizing the catch of the two species in the discrete prob distribution
AddNoFishing	integer [0,1], indicating whether to add a single patch that reflects no fishing, catch=0, effort=0
Spp1DiscardSteps	number of patches that reflect discarding species 1
Spp2DiscardSteps	number of patches that reflect discarding species 2
RIStar	integer[0,1] indicating whether the I* array shouold be returned to R, this is not possible for large problems, owing to memory restrictions
ChoiceDist	ouptut the treholds in the prob distribution for the landings?

Details

This function returns an object of class DynState with the decision array and the individual simulations through this array with information on the effort, catch rates and exceeding of quota.

Value

An object of class DynState.

Author(s)

Jan Jaap Poos

flr/FLRDynState documentation built on Sept. 6, 2021, 5:51 a.m.