aicbic: aicbic returns the AIC and BIC for a given model

In MQMF: Modelling and Quantitative Methods in Fisheries

aicbic returns the AIC and BIC for a given model

Description

aicbic calculates and returns the AIC and BIC using the standard definitions. It defaults to assuming that negative log- likelihoods have been used in the model fitting, but provides the option of having used SSQ (set nLL to FALSE). If using SSQ it uses Burnham and Anderson's (2002) definition but sets BIC to NA. aicbic can recognize the outputs from optim, nlm, and nlminb.

Usage

aicbic(model, dat, nLL = TRUE)

Arguments

model	the optimum model fitted by either optim, nlm, or nlminb
dat	the data set used in the modelling, or just n the number of observations; it can distinguish between them
nLL	uses negative log-likelihood? default=TRUE

Value

a vector of four numbers, AIC first, then BIC, then negLL or SSQ, depending on nLL, then number of parameters p

References

Burnham, K.P. and D.R. Anderson (2002) Model Selection and Inference. A Practical Information-Theoretic Approach. Second Edition Springer-Verlag, New York. 488 p.

Examples

data(blackisland); bi <- blackisland
param <- c(Linf=170.0,K=0.3,sigma=4.0)
modelvb <- nlm(f=negNLL,p=param,funk=fabens,observed=bi$dl,indat=bi,
               initL="l1",delT="dt") # could have used the defaults
# Do not worry about the warning messages
aicbic(modelvb,blackisland)  # 588.3382 596.3846 291.1691   3

MQMF documentation built on Sept. 8, 2023, 5:14 p.m.