fit_model {LogisticCopula}

fit_model

Description

This function updates the parameters of a LogisticCopula model by maximum likelihood.

Usage

fit_model(
  y,
  x,
  m_obj,
  maxit = 5,
  num_grad = FALSE,
  verbose = FALSE,
  hessian = FALSE,
  reltol = sqrt(.Machine$double.eps)
)

Arguments

y

A vector of n observations of the (univariate) binary outcome variable y

x

A (n x p) matrix of n observations of p covariates

m_obj

The model object as returned from fit_copula_interactions

maxit

The maximum number of gradient steps

num_grad

Whether to compute gradients numerically.

verbose

Whether information about the progress should be printed to the console.

hessian

Whether to numerically compute the hessian matrix, see the documentation for optim.

reltol

Relative convergence tolerance, see the documentation for optim.

Value

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.