aicbic {MQMF} | R Documentation |
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