BIC.remix {REMixed} | R Documentation |
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 class 'remix'
BIC(object, ...)
Arguments
object |
output of |
... |
additional arguments. |
Value
BIC.
References
Schwarz, G. 1978. Estimating the dimension of a model. The annals of statistics 6 (2): 461-464
Examples
## Not run:
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)
## End(Not run)
[Package REMixed version 0.1.0 Index]