groageexp {LifeHist}

Exploratory Growth Modeling with Age and Length Data

Description

For a data object of class 'GroAgeData' examine the goodness of initial guessed values of model parameters by making predictions and calculating residuals.

Usage

groageexp(x, m, unsex.action = NULL, par, distr)

Arguments

x

An object of class 'GroAgeData'.

m

Character, the specific growth model to be examined, either 'vonBer' (von Bertalanffy), 'schnute1', 'schnute2', or 'schnute3'

unsex.action

Character, optionally, when there are unsexed individual, what to do with these, either 'split' (random assignment of half to males and half to females), 'males' (complete assignment to males), 'females' (complete assignment to females), or 'ignore'.

par

Numeric, the logarithm of the vector of initial parameter values.

distr

Character, the distribution of the data, either 'apnormal' (adjusted profile approximation to the normal likelihood), 'aplnormal' adjusted profile approximation to the lognormal likelihood), 'normal', 'lognormal', or 'gamma'.

Details

When the distribution of the data is 'normal', 'lognormal', or 'gamma', an additional dispersion parameter has to be provided along with the growth model parameters, and placed at the end of the parameter vector.

Value

A list with class attribute 'GroAgeExp' with the following components:

Properties

Properties of the data, passed from 'x'

Data

A data.frame with age, observed length, predicted length, and 'deviance' residuals

Data

Optionally, the same as previous component but for the other sex

Note

Model types 'schnute1', 'schnute2', 'schnute3' have 5, 3, and 2 parameters respectively. 'schnute1' is described in Arkhipkin and Roa-Ureta (2005) whereas 'schnute2' and 'schnute3' are described in Roa-Ureta (2010).

Author(s)

Ruben H. Roa-Ureta

References

Arkhipkin, A., Roa-Ureta, R. 2005. Identification of growth models for squids. Marine and Freshwater Research 56:371-386.

Roa-Ureta, R. 2010. A likelihood-based model of fish growth with multiple length frequency data. Journal of Agricultural, Biological and Environmental Statistics 15:416-429

Examples

#Schnute - Normal
data(ksbream)
KSBream.AgeLen <- as.GroAgeData(x=ksbream,
                                sex="Total",
                                maleskey=1,
                                femaleskey=2,
                                coldate=1,
                                colsex=9,
                                colage=11,
                                collen=2,
                                colbw=5,
                                colliver=7,
                                colgonad=8,
                                lentype="Total",
                                unitsage="Years",
                                unitslen="mm",
                                unitsbw="g",
                                unitsliver="g",
                                unitsgonad="g",
                                spec="KSBream")
#par ini
l1.f  <- 175
a1.f  <- 1
mu.f  <- 250
g1.f  <- 0.15
g2.f  <- 0.1
l1.m  <- 175
a1.m  <- 1
mu.m  <- 210
g1.m  <- 0.25
g2.m  <- 0.1
psi.f <- 0.5
psi.m <- 0.45
par.ini <- log(c(l1.f,a1.f,mu.f,g1.f,g2.f,l1.m,a1.m,mu.m,g1.m,g2.m,psi.f,psi.m))
KSBream.AgeLen.exp <- groageexp(x=KSBream.AgeLen,
                                unsex.action="split",
                                m="schnute1",
                                par=par.ini,
                                distr="normal")
plot(KSBream.AgeLen.exp)