REMixed (version 1.1.2)

BIC.remix: BIC for remix object

Description

Computes bayesian information criterion from the output of remix as $$BIC = -2\mathcal{LL}_{y}(\hat\theta,\hat\alpha)+\log(N)P$$ where \(P\) is the total number of parameters estimated, \(N\) the number of subject and \(\mathcal{LL}_{y}(\hat\theta,\hat\alpha)\) the log-likelihood of the model.

Usage

# S3 method for remix
BIC(object, ...)

Value

BIC.

Arguments

object

output of remix.

...

additional arguments.

References

Schwarz, G. 1978. Estimating the dimension of a model. The annals of statistics 6 (2): 461-464

Examples

if (FALSE) {
project <- getMLXdir()

ObsModel.transfo = list(S=list(AB=log10),
                        linkS="yAB",
                        R=rep(list(S=function(x){x}),5),
                        linkR = paste0("yG",1:5))

alpha=list(alpha0=NULL,
           alpha1=setNames(paste0("alpha_1",1:5),paste0("yG",1:5)))

y = c(S=5,AB=1000)
lambda = 1440

res = remix(project = project,
            dynFUN = dynFUN_demo,
            y = y,
            ObsModel.transfo = ObsModel.transfo,
            alpha = alpha,
            selfInit = TRUE,
            eps1=10**(-2),
            eps2=1,
            lambda=lambda)

BIC(res)
}