Estimate marginal log posterior of a single BGNLM model with alternative defaults
estimate.gamma.cpen_2(
formula,
data,
r = 1/223,
logn = log(223),
relat = c("to23", "expi", "logi", "to35", "sini", "troot", "sigmoid")
)
A list of
marginal likelihood of the model
AIC model selection criterion
BIC model selection criterion
a vector of posterior modes of the parameters
formula
dataset
prior inclusion penalty parameter
logn
a set of nonlinear transformations in the class of BGNLMs of interest