This function updates the parameters of a LogisticCopula model by maximum likelihood.
fit_model(
y,
x,
m_obj,
maxit = 5,
num_grad = FALSE,
verbose = FALSE,
hessian = FALSE,
reltol = sqrt(.Machine$double.eps)
)A logistic_copula object, which contains the regression coefficients of the model, the parameters of the chosen conditional covariate distribution that corresponds to the regression coefficients, and the pair of vine-models that extend the logistic regression model.
A vector of n observations of the (univariate) binary outcome variable y
A (n x p) matrix of n observations of p covariates
The model object as returned from fit_copula_interactions
The maximum number of gradient steps
Whether to compute gradients numerically.
Whether information about the progress should be printed to the console.
Whether to numerically compute the hessian matrix, see the documentation for optim.
Relative convergence tolerance, see the documentation for optim.