MQMF (version 0.1.0)

aicbic: 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 three 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

# NOT RUN {
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
aicbic(modelvb,blackisland)  # 588.3382 596.3846 291.1691   3
# }