Estimate marginal log posterior of a single BGNLM model
estimate.gamma.cpen(
formula,
data,
r = 1/1000,
logn = log(1000),
relat = c("cos", "sigmoid", "tanh", "atan", "sin", "erf")
)
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