FLSR: Class FLSR
In flr/FLCore: Core Package of FLR, Fisheries Modelling in R

FLSR	R Documentation

Class FLSR

Description

Class for stock-recruitment models.

Usage

FLSR(model, ...)

## S4 method for signature 'ANY'
FLSR(model, ...)

## S4 method for signature 'missing'
FLSR(model, ...)

Details

A series of commonly-used stock-recruitment models are already available, including the corresponding likelihood functions and calculation of initial values. See SRModels for more details and the exact formulation implemented for each of them.

Slots

name: Name of the object (character).
desc: Description of the object (character).
range: Range (numeric).
rec: Recruitment series (FLQuant).
ssb: Index of reproductive potential, e.g. SSB or egg oor egg production (FLQuant).
fitted: Estimated values for rec (FLQuant).
residuals: Residuals obtained from the model fit (FLArray).
covar: Covariates for SR model (FLQuants).
model: Model formula (formula).
gr: Function returning the gradient of the likelihood (function).
logl: Log-likelihood function (function).
initial: Function returning initial parameter values for the optimizer (function).
params: Estimated parameter values (FLPar).
logLik: Value of the log-likelihood (logLik).
vcov: Variance-covariance matrix (array).
details: Extra information on the model fit procedure (list).
logerror: Is the error on a log scale (logical).
distribution: (factor).
hessian: Resulting Hessian matrix from the fit (array).

Author(s)

The FLR Team

Examples


  # Create an empty FLSR object.
  sr1 <- FLSR()

  # Create an  FLSR object using the existing SR models.
  sr2 <- FLSR(model = 'ricker')
  sr2@model
  sr2@initial
  sr2@logl

  sr3 <- FLSR(model = 'bevholt')
  sr3@model
  sr3@initial
  sr3@logl

  # Create an FLSR using a function.
  mysr1 <- function(){
    model <- rec ~ a*ssb^b
    return(list(model = model))}

  sr4 <- FLSR(model = mysr1)

  # Create an FLSR using a function and check that it works.
  mysr2 <- function(){
    formula <- rec ~ a+ssb*b

    logl <- function(a, b, sigma, rec, ssb) sum(dnorm(rec,
      a + ssb*b, sqrt(sigma), TRUE))

   initial <- structure(function(rec, ssb) {
      a   <- mean(rec)
      b   <- 1
      sigma <- sqrt(var(rec))

      return(list(a=a, b=b, sigma=sigma))},
        lower = c(0, 1e-04, 1e-04), upper = rep(Inf, 3))

   return(list(model = formula, initial = initial, logl = logl))
  }

  ssb <- FLQuant(runif(10, 10000, 100000))
  rec <- 10000 + 2*ssb + rnorm(10,0,1)
  sr5 <- FLSR(model = mysr2, ssb = ssb, rec = rec)

  sr5.mle <- fmle(sr5)
  sr5.nls <- nls(sr5)

# NS Herring stock-recruitment dataset
data(nsher)

# already fitted with a Ricker SR model
summary(nsher)

plot(nsher)

# change model
model(nsher) <- bevholt()

# fit through MLE
nsher <- fmle(nsher)

plot(nsher)

flr/FLCore documentation built on May 4, 2024, midnight