createInits: Method createInits
In flr/bbm: FLR Implementation of a Two-Stage Stock Assessment Model

createInits

R Documentation

Method createInits

Description

Function for generating intial values for the parameters of the bbm function, given information on catches, survey indices and instantaneous rate of biomass decrease, g.

Usage

createInits(object, indicesB, indicesP, ...)

## S4 method for signature 'FLQuant,FLQuants,FLQuants'
createInits(object, indicesB, indicesP, findicesB, findicesP, g)

## S4 method for signature 'FLStock,ANY,ANY'
createInits(object, indicesB, indicesP, findicesB = NULL, findicesP = NULL, g)

## S4 method for signature 'FLQuant,FLIndices,FLIndices'
createInits(object, indicesB, indicesP, findicesB = NULL, findicesP = NULL, g)

## S4 method for signature 'FLQuant,FLQuant,FLQuant'
createInits(object, indicesB, indicesP, findicesB, findicesP, g)

Arguments

`object`	An `FLQuant` with catch information (for recruits and adults) or an `FLStock`.
`indicesB`	Abundance indices in total biomass (element of class: `FLQuants`, `FLQuant` or `FLIndices`) from surveys. Please assign a survey name to each index.
`indicesP`	Percentage of recruits in biomass (element of class: `FLQuants`, `FLQuant` or `FLIndices`) from surveys. Please assign a survey name to each proportion.
`findicesB`	A `vector` with fraction of the year corresponding to each of the indicesB.
`findicesP`	A `vector` with fraction of the year corresponding to each of the indicesP.
`g`	A `vector` with information on instantaneous rate of biomass decrease, g = M - G, for recruits (rec) and adults (adult).

Value

An object of class FLPar.

Methods

Methods exist for various calculations based on the output class (FLPar). For details: ?FLPar.

Author(s)

Leire Ibaibarriaga & Sonia Sanchez.

Examples


# Load data
data(ane)


# Case: object='FLQuant'; indicesB=indicesP='FLQuants'
inits1 <- createInits( catch.ane,
                       indicesB=lapply( indicesB.ane, function(x) x@index), 
                       indicesP=lapply( indicesP.ane, function(x) x@index), 
                       findicesB=unlist(lapply( indicesB.ane, function(x) mean(range(x)[c('startf','endf')]))),
                       findicesP=unlist(lapply( indicesP.ane, function(x) mean(range(x)[c('startf','endf')]))), 
                       g=control.ane@g )
class(inits1)

# Case: object='FLQuant'; indicesB=indicesP='ANY'

stock <- FLStock(catch.n=catch.ane, catch.wt=catch.ane*0+1)
units(stock@catch.wt) <- ''
stock@catch <- quantSums(stock@catch.n*stock@catch.wt)

inits2 <- createInits( stock, indicesB=indicesB.ane, indicesP=indicesP.ane, 
                       g=control.ane@g )
class(inits2)

# Case: object='FLQuant'; indicesB=indicesP='FLIndices'

inits3 <- createInits( catch.ane,
                       indicesB=indicesB.ane, indicesP=indicesP.ane, 
                       g=control.ane@g )
class(inits3)

# Case: object='FLQuant'; indicesB=indicesP='FLQuant'
inits4 <- createInits( catch.ane,
                       indicesB=indicesB.ane[[1]]@index, indicesP=indicesP.ane[[1]]@index, 
                       findicesB=c( depm=(indicesB.ane[[1]]@range[['startf']]+indicesB.ane[[1]]@range[['endf']])/2),
                       findicesP=c( depm=(indicesP.ane[[1]]@range[['startf']]+indicesP.ane[[1]]@range[['endf']])/2), 
                       g=control.ane@g )
class(inits4)

# Run assessment (with the different initial values)
run0 <- bbm(catch.ane, indicesB=indicesB.ane, indicesP=indicesP.ane, control=control.ane, inits=inits.ane)
run1 <- bbm(catch.ane, indicesB=indicesB.ane, indicesP=indicesP.ane, control=control.ane, inits=inits1)
run2 <- bbm(catch.ane, indicesB=indicesB.ane, indicesP=indicesP.ane, control=control.ane, inits=inits2)
run3 <- bbm(catch.ane, indicesB=indicesB.ane, indicesP=indicesP.ane, control=control.ane, inits=inits3)
namdel <- c("q_acoustic","psi_acoustic","xi_acoustic") # we will take only one of the indices --> need to delete the parameters related to other indices
control <- control.ane
control@param.fix <- control@param.fix[dimnames(control@param.fix)$params[!dimnames(control@param.fix)$params %in% namdel],]
run4 <- bbm(catch.ane, indicesB=indicesB.ane[[1]]@index, indicesP=indicesP.ane[[1]]@index, 
            findicesB=c( depm=(indicesB.ane[[1]]@range[['startf']]+indicesB.ane[[1]]@range[['endf']])/2),
            findicesP=c( depm=(indicesP.ane[[1]]@range[['startf']]+indicesP.ane[[1]]@range[['endf']])/2), 
            control=control, inits=inits4)

# Plot assessed populations
biomass <- FLQuants()
runs <- paste("run",0:4,sep="")
names(runs) <- c('bc','run1','run2','run3','only_depm')
for (i in 1:length(runs)) biomass[[i]] <- quantSums(stock.bio(get(runs[i])))
names(biomass) <- names(runs)
plot( biomass)

flr/bbm documentation built on Sept. 6, 2022, 8:56 p.m.